EP2587264A1 - Method and use of metabolites for the diagnosis and differentiation of neonatal encephalopathy - Google Patents

Method and use of metabolites for the diagnosis and differentiation of neonatal encephalopathy Download PDF

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EP2587264A1
EP2587264A1 EP11008563.6A EP11008563A EP2587264A1 EP 2587264 A1 EP2587264 A1 EP 2587264A1 EP 11008563 A EP11008563 A EP 11008563A EP 2587264 A1 EP2587264 A1 EP 2587264A1
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met
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carnosine
metabolites
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French (fr)
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Priority to EP11008563.6A priority Critical patent/EP2587264A1/en
Priority to ES12778117T priority patent/ES2927921T3/en
Priority to EP12778117.7A priority patent/EP2771696B1/en
Priority to CA2886644A priority patent/CA2886644A1/en
Priority to PCT/EP2012/071174 priority patent/WO2013060788A2/en
Priority to US14/353,969 priority patent/US10514383B2/en
Priority to DK12778117.7T priority patent/DK2771696T3/en
Publication of EP2587264A1 publication Critical patent/EP2587264A1/en
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    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/68Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving proteins, peptides or amino acids
    • G01N33/6893Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving proteins, peptides or amino acids related to diseases not provided for elsewhere
    • G01N33/6896Neurological disorders, e.g. Alzheimer's disease
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N27/00Investigating or analysing materials by the use of electric, electrochemical, or magnetic means
    • G01N27/26Investigating or analysing materials by the use of electric, electrochemical, or magnetic means by investigating electrochemical variables; by using electrolysis or electrophoresis
    • G01N27/416Systems
    • G01N27/447Systems using electrophoresis
    • GPHYSICS
    • G16INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16BBIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B20/00ICT specially adapted for functional genomics or proteomics, e.g. genotype-phenotype associations
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2800/00Detection or diagnosis of diseases
    • G01N2800/28Neurological disorders
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2800/00Detection or diagnosis of diseases
    • G01N2800/38Pediatrics
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2800/00Detection or diagnosis of diseases
    • G01N2800/60Complex ways of combining multiple protein biomarkers for diagnosis
    • GPHYSICS
    • G16INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16CCOMPUTATIONAL CHEMISTRY; CHEMOINFORMATICS; COMPUTATIONAL MATERIALS SCIENCE
    • G16C20/00Chemoinformatics, i.e. ICT specially adapted for the handling of physicochemical or structural data of chemical particles, elements, compounds or mixtures
    • G16C20/70Machine learning, data mining or chemometrics

Definitions

  • the invention generally relates to the identification of metabolites and signatures (panels) of metabolites, which are applicable as biomarkers in clinical diagnosis, in particular for neonatal encephalopathy. They are useful tools in differential clinical diagnosis for early detection of brain tissues affected by brain damage and may also be applied in diagnosing disease progression and determination of affected brain areas and determination of associated adverse neurological outcome.
  • the present invention more particularly relates to an in vitro method for predicting the likelihood of neonatal encephalopathy of distinct brain areas, identification of affected brain area(s) of neonatal encephalopathy and risk of brain damage and prognosis and neurological outcome due to identification of the type and extent of damage of distinct brain tissues, in particular of hippocampus and / or basal ganglia.
  • Neonatal encephalopathy is a serious condition with life long consequences. NE is the most important cause of morbidity and mortality in the term born baby. About 10% of those affected die and 25% are severely handicapped due to long-term complications such as cerebral palsy, mental retardation with learning difficulties, cerebral visual impairments and/or epilepsy. Its long-term consequences impose a large burden on the child and family and on worldwide healthcare budgets. The estimated costs of the treatment of sequelae of NE in the US is around 750 000 US $ per patient.
  • One major reason for NE is pre-, peri- and postnatal asphyxia, a condition in which the fetus or newborn lacks oxygen.
  • hypothermia whole body hypothermia or selective head cooling
  • perinatal asphyxia in term born neonates.
  • the effect of moderate hypothermia was found to be associated with a moderate reduction in death and neurological impairment at 18 months. It is of outmost importance that the therapeutic benefit of hypothermia is strongly dependent on the time point of its initiation. The earlier the diagnosis is made and the early therapy can be started the more neuroprotection can be achieved. Accordingly, early detection of neonatal encephalopathy and severity assessment is vital to therapeutic success.
  • the diagnostic criteria for neonatal encephalopathy in term newborn infants require i) signs of perinatal and postnatal asphyxia, abnormal blood gas values (increase in base deficit, blood lactate values, low cord pH in the umbilical artery (UApH) and need for resuscitation, and ii) signs of brain involvement and abnormal neurology characterized by neurological scores (Sarnat or Thompson score) and any presence of seizure activity and iii) demonstrating electroencephalographic evidence of abnormal cerebral function by means of the amplitude-integrated or ten-lead standard EEG.
  • aEEG amplitude integrated EEG
  • the process of implementation of the aEEG and the evaluation of the signal takes at least 30 to 45 minutes. This is of particular importance since it is known that treatment is more effective the earlier it is initiated. Imaging technologies such as MRT (Magnetic Resonance Tomography), however, are applicable from day three after birth only and therefore, are not useful for early diagnosis and timely therapy.
  • MRT Magnetic Resonance Tomography
  • the medical practitioner uses a number of diagnostic tools for diagnosing a patient suffering from a certain disease.
  • diagnostic tools for diagnosing a patient suffering from a certain disease.
  • measurement of a series of single routine parameters, e.g. in a blood sample is a common diagnostic laboratory approach.
  • These single parameters comprise for example enzyme activities and enzyme concentration and/or enzyme detection
  • WO 2010/128054 A1 corresponding to EP 2 249 161 A1 , describes a method of diagnosing asphyxia.
  • said document refers to a method for in vitro diagnosing e.g. perinatal asphyxia and disorders related to hypoxia, characterized by quantitatively detecting in at least one biological sample of at least one tissue of a mammalian subject a plurality of asphyxia specific compounds having a molecular weight of less than 1500 Dalton, except lactate, comprising the steps of:
  • WO 2010/128054 A1 uses asphyxia specific compounds as biomarkers which are endogenous compounds being selected from the group consisting of: biogenic amines; carnitine-derived compounds; amino acids; bile acids; carboxylic acids; eicosanoids; lipids; precursors of cholesterol, cholesterol metabolites, prostanoids; and sugars. Furthermore, WO 2010/128054 A1 relates to a method of in vitro estimating duration of hypoxia in a patient, a method for in vitro monitoring of normoxic, hypoxic and hyperoxic conditions and/or normobaric and hyperbaric oxygen therapy and a kit for carrying out the methods thereof.
  • amino acids particularly branched chained amino acids, metabolites of the Krebs cycle, including alpha-ketoglutarate, succinate and fumarate, biogenic amines, bile acids, prostaglandins, sphingolipids, glycerophospholipids, oxysterols and acylcarnitines.
  • Assessment of brain injuries per se, or biomarkers to detect brain injuries per se are not comprised by the Solberg et al. paper (cf. page 9, left column, lines 2-3), and identification or differentiation of brain areas or tissues or assessment of neurological outcome is not addressed.
  • Beckstrom et al. J ChromatogrA, 2011 Vol 1218, 1899-1906 evaluated whether metabolomic profiling can reveal metabolite changes in plasma after asphyxia in a Macaca nemestrina model of perinatal asphyxia.
  • the metabolic profile of post-asphyxia samples showed marked variability compared to the pre-asphyxia samples.
  • This metabolomic analysis confirmed lactate and creatinine as markers of asphyxia and discovered new metabolites including succinic acid and malate (intermediates in the Krebs cycle) and arachidonic acid (a brain fatty acid and inflammatory marker). Although these metabolite changes reflect the changes of asphyxia (similarly to the publication of Solberg et.al.), the metabolite changes were not related to brain injury, to identification or differentiation of brain areas or tissues or assessment of neurological outcome.
  • Said metabolite combinations comprise lactic acid in combination with one or more of 3-hydroxybutyric acid, 3-hydroxyisovaleric acid, methylmalonic acid, 4-hydroxyphenyllactic acid, and 5-oxoproline. Again, all of these metabolites we determined only in urine samples, and, moreover, not within the first hours of life.
  • the problem underlying the present invention is to provide an early diagnostic approach for assessing NE in infants with high sensitivities and specificities, capable of determining brain tissues involved and/or brain tissues damaged and/or prone to subsequent future damage and/or predict neurological outcome.
  • the present invention relates to markers of NE, in particular of brain injury and neurological behavioural outcome in infants, its severity and distribution (affected brain areas).
  • the present invention provides metabolites that are differentially present in infants affected by NE.
  • the present invention also identifies a series of metabolites (or signatures of metabolites) as being differentially present in subjects depending on the severity of brain injury in basal ganglia, hippocampus or other distinct brain tissues and neurological outcome.
  • the present invention thus provides a solution to the aforementioned diagnostic problems based on the application of a new technology in this context and on previously unknown lists of endogenous metabolites as diagnostic marker for the identification NE and of affected brain tissues. Since metabolite concentration differences in biological fluids and tissues provide links to the various phenotypical responses, metabolites are suitable biomarker candidates.
  • the present invention allows for an early accurate, rapid, and sensitive prediction and diagnosis of NE in infants with an assignment of damage to distinct brain tissues and assessment of neurological outcome, in particular but not limited to hippocampus and basal ganglia through a measurement of a plurality (2 or more) of endogenous metabolic biomarker (metabolites) taken from a biological sample at a single point in time.
  • the reference biomarker values may be obtained from a population of individuals (a "reference population") who are, for example, afflicted with brain injury assigned to affected brain tissues, in particular hippocampus und basal ganglia, or who are suffering from brain injury assignable to distinct brain tissues or a particular stage in the progression of brain injury.
  • biomarker panel values or score from the individual contains appropriately characteristic features of the biomarker values or scores from the reference population, then the individual is diagnosed as being likely of having or developing brain injury assignable but not limited to damage of hippocampus and or basal ganglia brain tissues, as being afflicted with brain injury attributable but not limited to damage of hippocampus and/or basal ganglia brain tissues allowing also an assessment of neurological outcome.
  • Neonatal encephalopathy in the context of the present invention is defined as disturbed neurological function in the earliest days of life in the newborn infant resulting in long-term adverse neurological, psychological and neurobehavioral adverse outcome.
  • NE can result from a wide variety of conditions and often remains unexplained. Given that the underlying nature of brain injury causing neurologic impairment in a newborn is often poorly understood, NE has emerged as the preferred terminology to describe central nervous system dysfunction in the newborn period, as it does not imply a specific underlying pathophysiology.
  • Brain injury or " brain damage” in the context of the present invention is defined as the occurrence of increased cell death by apoptosis and necrosis in any brain area of any cell type and abnormal neuronal function and network compared to healthy controls. Brain injury is assessed with the aEEG for both EEG pattern and epileptic activity, with a clinical neurological score, by histology (haematoxylin and eosin staining) and for caspase-3 activity in 4 cortical areas.
  • Table 1 Short names of chemical compounds (metabolites or metabolic markers) as analysed in the context of the present invention Short Name Common name Chemical class Chemical class short Potential CAS-Number alpha-KGA alpha-Ketoglutaric acid dicarboxylic acids En.Met 328-50-7 Fum Fumaric acid dicarboxylic acids En.Met 110-17-8;110-16-7 Hex-P Hexosephosphate (e.g.
  • Glucose-1-phosphate + Glucose-6-phosphate + Fructose-6-phosphate) sugars En.Met 56-73-5;643-13-0;59-56-3;3672-15-9;2255-14-3;27251-84-9;55607-88-0;15978-08-2;53798-20-2;19046-69-6;2255-14-3 Lac Lactate sugars En.Met 79-33-4;10326-41-7;503-66-2;50-21-5 Pent-P Pentosephosphate (e.g.
  • Ribose-5-phosphate + Ribulose-5-phosphate) sugars En.Met 3615-55-2;4300-28-1;4151-19-3;14075-00-4;13137-52-5 OAA Pyruvate + Oxaloacetate carboxylic acids
  • En.Met 328-42-7 Suc Succinic acid dicarboxylic acids
  • En.Met 110-15-6 C0 Carnitine (free) acylcarnitines Ac.Ca. 541-14-0;541-15-1;406-76-8 C10 Decanoylcamitine [Caprylcarnitine] (Fumarylcarnitine) acylcarnitines Ac.Ca.
  • C5 Isovalerylcarnitine / 2-Methylbutyrylcarnitine / Valerylcarnitine acylcarnitines Ac.Ca. 31023-24-2;31023-25-3
  • C5:1-DC Glutaconylcarnitine / Mesaconylcarnitine (Undecanoylcarnitine) acylcarnitines Ac.Ca.
  • C5-DC (C6-OH) Glutarylcarnitine acylcarnitines Ac.Ca.
  • SM (OH) C22:1 Hydroxysphingomyelin with acyl residue sum C22:1 sphingolipids S.L. SM (OH) C22:2 Hydroxysphingomyelin with acyl residue sum C22:2 sphingolipids S.L. SM (OH) C24:1 Hydroxysphingomyelin with acyl residue sum C24:1 sphingolipids S.L. Ala Alanine aminoacids Am.Ac. 56-41-7;107-95-9;338-69-2;302-72-7 Arg Arginine aminoacids Am.Ac. 74-79-3;157-06-2;7200-25-1 Asn Asparagine aminoacids Am.Ac.
  • metabolite or " metabolic marker” or “ low molecular weight metabolic marker” denotes endogenous organic compounds of a cell, an organism, a tissue or being present in body liquids, in particular blood, and in extracts or fractions obtained from the aforementioned sources.
  • Typical examples of metabolites are carbohydrates, lipids, phospholipids, sphingolipids and sphingophospholipids, amino acids, cholesterol, steroid hormones and oxidized sterols and other compounds such as collected in the Human Metabolite database [ Wishart DS et al., HMDB: the Human Metabolome Database. Nucleic Acids Res.
  • Hippocampus-specific metabolites are listed in subsequent Table 2. These metabolites, individually or combinations of several of such metabolites, may be applied as markers for brain injury affecting the hippocampus of an infant.
  • Table 2 " Hippocampus-specific" metabolites No Short name Full name Contribution 1 Lac Lactate + 2 Fum Fumaric acid + 3 Ac-Orn N-acetylornithine + 4 Carnosine Carnosine - 5 C5:1-DC Glutaconylcarnitine / Mesaconylcarnitine (Undecanoylcarnitine) + 6 C16:2 Hexadecadienoylcarnitine + 7 Pent-P Pentosephosphate (e.g.
  • Basal ganglia-specific metabolites are listed in subsequent Table 3. These metabolites, individually or combinations of several of such metabolites, may be applied as markers for brain injury affecting basal ganglia of an infant.
  • the present invention also refers to " Neurological behavioural score-specific" metabolites. They are listed in subsequent Table 4. These metabolites, individually or combinations of several of such metabolites, may be applied as markers for neurological behavioural deficits of an infant. Table 4: " Neurological behavioural score-specific" metabolites No.
  • Metabolomics designates the comprehensive qualitative, or in particular quantitative measurement of several metabolites as defined herein; in particular by, but not limited to, analytical methods such as mass spectrometry, coupling of liquid chromatography, gas chromatography and other separation methods, like chromatography with mass spectrometry.
  • metabolism refers to the chemical changes that occur within the tissues of an organism, including “ anabolism” and “ catabolism” .
  • Anabolism refers to biosynthesis or the buildup of molecules and catabolism refers to the breakdown of molecules.
  • a “biomarker” in this context is a characteristic, comprising concentration data of at least two, as for example 2, 3, 4, 5, 6, 7, 8, 9 or 10, metabolites (also designated as a " panel” of metabolites, “ signature” of metabolites, “ model” or” profile” using quantitative data or concentration data directly or processed by any mathematical transformation (e.g. by a classification method) and evaluated as an indicator of biologic processes, pathogenic processes, or responses to a therapeutic intervention associated with NE in infants.
  • a " score" in the context of the invention denotes a value, in particular a quantitative value, generated from metabolite data by means of any mathematical transformation or by subjecting to any mathematical equation and comparing these data to data or mathematically transformed or processed data of a reference population.
  • the " onset of NE in infants" refers to an early stage of NE in infants, i.e., prior to a stage when the clinical manifestations are sufficient to support a clinical suspicion of brain injury in infants.
  • the exact mechanism by which a patient acquires NE in infants is not a critical aspect of the invention.
  • the methods of the present invention can detect changes in the biomarker score independent of the origin of the brain injury in infants. Regardless of how NE in infants arises (as for example by asphyxia, hypoxia and/or ischemia), the methods of the present invention allow for determining the status of a patient having, or suspected of having, NE, as classified by previously used criteria.
  • NE in infants-specific metabolite refers to metabolites that are differentially present or differentially concentrated in an infant suffering from NE compared to healthy infant.
  • a "specific metabolite” or " NE in infants- specific metabolite” is preferably differentially present at a level that is statistically significant (e.g., an adjusted p-value less than 0.05 as determined using either linear model including Analysis of Variance and Welch' s t-test or its non parametric equivalent versions). Exemplary NE in infants - specific metabolites are described herein.
  • NE in infants- specific metabolites encompass the groups of " hippocampus-specific” (or “ hippocampus damage-specific” ), “ basal-ganglia-specific” (or “ basal ganglia damage-specific” ) or “ Neurological behavioural score-specific” metabolites (see Tables 2, 3 and 4).
  • a " biological sample” may contain any biological material suitable for detecting the desired biomarkers, and may comprise cellular and/or non-cellular material from a subject.
  • the sample can be isolated from any suitable biological tissue or body fluid such as, for example, tissue, and, in particular, blood, blood plasma, and blood serum.
  • the sample may be analyzed without or after a pre-treatment.
  • pre-treated samples are pre-treated blood, like EDTA-blood, or EDTA-plasma, citrate-plasma, heparin plasma.
  • the originally obtained samples or fractions thereof may be further modified by methods known in the art, as for example by fractionation or dilution. Fractionation may be performed to remove constituents which might disturb the analysis.
  • Dilution may be performed by mixing, the original sample or fraction with a suitable sample liquid, like a suitable buffer, in order to adjust the concentration the constituents, as for example of the analyte.
  • a suitable sample liquid like a suitable buffer
  • Such modified samples exemplify samples " derived from" the original body fluid sample collected or isolated from the body of the individual.
  • a " reference level" of a metabolite means a level of the metabolite that is indicative of a particular disease state, phenotype, or lack thereof, as well as combinations of disease states, phenotypes, or lack thereof.
  • a " positive" reference level of a metabolite means a level that is indicative of a particular disease state or phenotype.
  • a “ negative” reference level of a metabolite means a level that is indicative of a lack of a particular disease state or phenotype.
  • a " NE in infants- positive reference level" of a metabolite means a level of a metabolite that is indicative of a positive diagnosis of NE in infants in a subject
  • a " NE in infants- negative reference level" of a metabolite means a level of a metabolite that is indicative of a negative diagnosis of NE in infants in a subject.
  • a " reference level" of a metabolite may be an absolute or relative amount or concentration of the metabolite, a presence or absence of the metabolite, a range of amount or concentration of the metabolite, a minimum and/or maximum amount or concentration of the metabolite, a mean amount or concentration of the metabolite, and/or a median amount or concentration of the metabolite; and, in addition, " reference levels" of combinations of metabolites may also be ratios of absolute or relative amounts or concentrations of two or more metabolites with respect to each other or a composed value / score obtained by a statistical model.
  • processor refers to a device that performs a set of steps according to a program (e.g., a digital computer).
  • processors for example, include Central Processing Units (" CPUs" ), electronic devices, or systems for receiving, transmitting, storing and/or manipulating data under programmed control.
  • CPUs Central Processing Units
  • electronic devices or systems for receiving, transmitting, storing and/or manipulating data under programmed control.
  • memory device refers to any data storage device that is readable by a computer, including, but not limited to, random access memory, hard disks, magnetic (floppy) disks, compact discs, DVDs, magnetic tape, flash memory, and the like.
  • Mass Spectrometry is a technique for measuring and analysing molecules that involves fragmenting a target molecule, then analysing the fragments, based on their mass/charge ratios, to produce a mass spectrum that serves as a " molecular fingerprint” . Determining the mass/charge ratio of an object is done through means of determining the wavelengths at which electromagnetic energy is absorbed by that object. There are several commonly used methods to determine the mass to charge ratio of an ion, some measuring the interaction of the ion trajectory with electromagnetic waves, others measuring the time an ion takes to travel a given distance, or a combination of both. The data from these fragment mass measurements can be searched against databases to obtain definitive identifications of target molecules.
  • separation refers to separating a complex mixture into its component proteins or metabolites.
  • Common laboratory separation techniques include gel electrophoresis and chromatography.
  • capillary electrophoresis refers to an automated analytical technique that separates molecules in a solution by applying voltage across buffer-filled capillaries. Capillary electrophoresis is generally used for separating ions, which move at different speeds when the voltage is applied, depending upon the size and charge of the ions. The solutes (ions) are seen as peaks as they pass through a detector and the area of each peak is proportional to the concentration of ions in the solute, which allows quantitative determinations of the ions.
  • chromatography refers to a physical method of separation in which the components to be separated are distributed between two phases, one of which is stationary (stationary phase) while the other (the mobile phase) moves in a definite direction. Chromatographic output data may be used for manipulation by the present invention.
  • a " mass spectrum” is a plot of data produced by a mass spectrometer, typically containing m/z values on x-axis and intensity values on y-axis.
  • a "peak" is a point on a mass spectrum with a relatively high y-value.
  • m/z refers to the dimensionless quantity formed by dividing the mass number of an ion by its charge number. It has long been called the " mass-to-charge” ratio.
  • detect may describe either the general act of discovering or discerning or the specific observation of a detectable compound or composition or metabolite or biomarker.
  • Assessing or “ assessment” is intended to include both quantitative and qualitative determination in the sense of obtaining an absolute value for the amount or concentration of the metabolite or metabolites to be analyzed present in the sample, and also obtaining an index, ratio, percentage or other value indicative of the level of metabolite in the sample.
  • Assessment may be direct or indirect and the chemical species actually detected need not of course be the analyte itself but may for example be a derivative thereof.
  • the purpose of such assessment of metabolite(s) may be different.
  • an assessment may be performed for evaluating the likelihood (or risk) of brain damage or encephalopathy to occur in a patient.
  • Purpose of an assessment may also be the determination of the severity (severity assessment) of brain damage or encephalopathy (optionally already diagnosed) and long-term neurological outcome in a patient. Assessment also encompasses the analysis of progression or regression of brain damage or encephalopathy. Assessment in the context of the invention also encompasses identification and/or differentiation of brain areas (as, for example, hippocampus and basal ganglia) affected (optionally to a different extent) by said damage.
  • patient refers in particular to a “ neonatal” patient, in particular pre-term born, or term born baby.
  • clinical failure refers to a negative outcome following NE treatment in infants.
  • the present invention provides methods and compositions for
  • a method of diagnosing (or aiding in diagnosing) whether a subject has NE comprises detecting the presence or absence or a differential level of a plurality of metabolites being specific for brain injury in basal ganglia, hippocampus or other distinct brain tissues in infants or specific for adverse neurological outcome in infants and diagnosing brain injury in basal ganglia, hippocampus or other distinct brain tissues in infants or adverse neurological outcome in infants based on the presence, absence or differential concentration levels of these compounds.
  • the presence, absence or concentration changes of these endogenous metabolites is used for differentiation of damaged brain regions and damaged brain tissues.
  • Such specific metabolites are selected from Tables 2, 3 or 4.
  • a computer-based analysis program is used to translate the raw data generated by the detection assay (e.g., the presence, absence, or amount of a NE specific metabolite) into data of predictive value for a clinician.
  • the clinician can access the predictive data using any suitable means.
  • the present invention provides the further benefit that the clinician, who is not likely to be trained in metabolite analysis, need not understand the raw data.
  • the data is presented directly to the clinician in its most useful form. The clinician is then able to immediately utilise the information in order to optimise the care of the subject.
  • the present invention contemplates any method capable of receiving, processing, and transmitting the information to and from laboratories conducting the assays, information providers, medical personal, and subjects.
  • the profile data is then prepared in a format suitable for interpretation by a treating clinician.
  • the prepared format may represent a diagnosis or risk assessment (e.g., likelihood of NE in infants being present) for the subject, along with recommendations for particular treatment options.
  • the data may be displayed to the clinician by any suitable method.
  • the profiling service generates a report that can be printed for the clinician (e.g., at the point of care) or displayed to the clinician on a computer monitor.
  • the information is first analysed at the point of care or at a regional facility.
  • the raw data is then sent to a central processing facility for further analysis and/or to convert the raw data to information useful for a clinician or patient.
  • the central processing facility provides the advantage of privacy (all data is stored in a central facility with uniform security protocols), speed, and uniformity of data analysis.
  • the central processing facility can then control the fate of the data following treatment of the subject. For example, using an electronic communication system, the central facility can provide data to the clinician, the subject, or researchers.
  • the amounts or levels of a plurality of metabolites in the sample may be compared to NE metabolite-reference levels, such as NE in infants-positive and/or NE in infants-negative reference levels to aid in diagnosing or to diagnose whether the subject has NE.
  • Levels of the plurality of metabolites in a sample corresponding to the NE in infants-positive reference levels are indicative of a diagnosis of NE in infants in the subject.
  • levels of a plurality metabolites that are differentially present (especially at a level that is statistically significant) in the sample as compared to NE in infants-negative reference levels are indicative of a diagnosis of NE in the subject.
  • levels of the two or more metabolites that are differentially present (especially at a level that is statistically significant) in the sample as compared to NE-positive respectively brain injury in a distinct brain tissue positive reference levels are indicative of a diagnosis of no brain injury in infants in the subject.
  • the level(s) of a plurality of the metabolites may be compared to NE in infants -positive respectively brain injury in a distinct brain tissue positive and/or NE -negative reference levels using various techniques, including a simple comparison (e.g., a manual comparison) of the level(s) of the one or more metabolites in the biological sample to NE -positive and/or NE -negative reference levels.
  • the level(s) of the one or more metabolites in the biological sample may also be compared to NE in infants-positive respectively brain injury in a distinct brain tissue positive and/or brain injury in infants - negative reference levels using one or more statistical analyses (e.g., linear models, t-test, logistic regression, Wilcoxon's rank sum test, decision tree, linear discriminant analysis, k nearest neighbours etc.).
  • statistical analyses e.g., linear models, t-test, logistic regression, Wilcoxon's rank sum test, decision tree, linear discriminant analysis, k nearest neighbours etc.
  • Embodiments of the present invention provide for multiplex or panel assays that simultaneously detect a plurality (at least two) of the markers of the present invention depicted in table 1, 2, 3 or 4.
  • panel or combination assays are provided that detected 2 or more, 3 or more, 4 or more, 5 or more, 6 or more, 7 or more, 8 or more, 9 or more, 10 or more, 5 or more markers in a single assay.
  • Non-limiting examples of panels are given in Tables 8, 9, 10, 11, 12 or 13.
  • assays are automated or high-throughput.
  • the present invention also relates to a method for predicting neurological outcome due to NE in infants characterized by in vitro detecting, in particular quantitatively, in at least one biological sample of a neonate patient a plurality of, like 2, 3, 4, 5, 6, 7, 8, 9 or 10, compounds being associated with, in particular specific for NE, and having a molecular weight of less than about 1500 Dalton (like in the range of 50 to 1500), comprising the steps of:
  • the levels of one or more of the recited metabolites may be determined in the methods of the present invention. For example, the level(s) of one metabolites, two or more metabolites, three or more metabolites, four or more metabolites, five or more metabolites, six or more metabolites, seven or more metabolites, eight or more metabolites, nine or more metabolites, ten or more metabolites, etc., including a combination of some or all of the metabolites including, but not limited to those listed in Table 4, may be determined and used in such methods.
  • Determining levels of combinations of the metabolites may allow greater sensitivity and specificity in the methods, such as diagnosing NE related to brain damage of basal ganglia and or hippocampus or for determining neurological outcome and aiding in the diagnosis of NE, and may allow better differentiation or characterisation of NE due to damage of distinct brain tissues from other disorders that may have similar or overlapping metabolites to NE due to damage of distinct brain tissues such as - but not limited to - basal ganglia and or hippocampus (as compared to a subject not having brain damage or having brain damage due to damage of other brain tissues). Determining levels of combinations of the metabolites may also allow greater sensitivity and specificity in the methods for determining neurological outcome.
  • the present invention provides, inter alia, methods of predicting the extent of brain damage and therefore the likelihood of an onset of NE together with an identification of damaged brain tissues such as - but not limited to - hippocampus tissue and or basal ganglia in an individual.
  • the invention further provides methods for predicting the neurological outcome due to brain damage and therefore the likelihood of NE.
  • the methods of the invention may also comprise obtaining a biomarker score at a single point of time from the individual and comparing the individual's biomarker profile to a reference biomarker profile. Comparison of the biomarker profiles can predict the onset of NE in the individual preferably with an accuracy of at least about 75%. This method may be repeated again at any time prior to the onset of NE in infants.
  • the present invention provides a method of diagnosing NE in infants related to damage of distinct brain tissues such as - but not limited to - hippocampus and or basal ganglia -in an individual having or suspected of having NE in infants.
  • This method comprises obtaining a biomarker score (as for example selected from the scores or models as listed in the attached tables 8, 9, 11 or 12) at a single point in time from the individual and comparing the individual's biomarker score to a reference biomarker score. Comparison of the biomarker profiles can diagnose NE in infants in the individual with an accuracy of at least about 75 %. This method may also be repeated on the individual at any time.
  • the present invention further provides a method of determining the progression (i.e., the stage) of NE involving distinct brain tissues such as, but not limited to, basal ganglia and or hippocampus in an individual.
  • This method comprises obtaining a biomarker profile composed of concentrations of metabolites (two or more) selected from Tables 2 or 3 (or selected from the scores or models as listed in the attached tables 8, 9, 11 or 12) at a single point in time from the individual and comparing the individual's biomarker profile to a reference biomarker score. Comparison of the biomarker scores can determine the progression of NE related to damaged brain tissues in individual infants preferably with an accuracy of at least about 75%. This method may also be repeated on the individual at any time.
  • the present invention provides, inter alia, a method of determining the status of NE in infants or diagnosing NE related to damage of distinct brain areas in infants.
  • the method comprises comparing a measurable characteristic of more than one metabolite of a metabolite biomarker panel or biomarker score composed of (processed or unprocessed) values of this panel obtained from a biological sample from the individual infant and a biomarker score obtained from biological samples from a reference population. Based on this comparison, the individual is classified as belonging to or not belonging to the reference population. The comparison, therefore, determines the likelihood of NE in infants due to likely damage of distinct brain tissues or diagnoses of such NE in infants in the individual.
  • the biomarkers in one embodiment, are selected from the list of metabolites shown in Tables 2 or 3 or, for example, are selected from the scores or models as listed in the attached tables 8, 9, 11 or 12 .
  • the present invention also provides methods for predicting NE related to damage of hippocampus and or basal ganglia tissue in infants. Such methods comprise the steps of: analyzing a biological sample from a subject to determine the levels of more than one metabolites for NE in infants in the sample, where the one or more metabolites are selected from Tables 2 and 3 (or are, for example, selected from the scores or models as listed in the attached tables 8, 9, 11 or 12) and comparing the levels of the metabolites, as well as a composed value / score generated by subjecting the concentrations of individual metabolite in the sample to a classification method such as affording an equation to process single concentration values - to obtain a separation between both (diseased and healthy) groups or comparing the level(s) of the one or more metabolites in the sample to NE positive or NE negative reference levels of the two or more metabolites in order to determine whether the subject is developing NE related to damage of hippocampus, basal ganglia or other distinct brain tissues.
  • the above methods for determining progression, status of disease or predicting disease may also be applied to the aspect of the invention related to neurological behavioural damages or deficits.
  • one or more metabolites as listed in Table 4 or one or more metabolite combinations listed in Table 10 or 13 may be applied accordingly.
  • the present invention provides a method of diagnosing brain damage in infants and/or duration/severity of brain damage of distinct brain areas, identification of affected area(s) of NE and risk of neonatal encephalopathy and prognosis and neurological outcome due to identification of type and extent of damage of distinct brain tissues, in particular of hippocampus and / or basal ganglia comprising: detecting (the presence or absence of 2 or more, 3 or more, 5 or more, 10 or more, etc.
  • metabolites measured together in a multiplex or panel format brain damage in infants specific metabolites in a sample (e.g., a tissue (e.g., biopsy) sample, a blood sample, a serum sample) from a subject; and diagnosing brain damage in the aforementioned brain tissues in infants based on the presence of specific metabolites.
  • a sample e.g., a tissue (e.g., biopsy) sample, a blood sample, a serum sample
  • the invention uses analytical kits, comprising
  • the present invention provides a solution to the problems described above, and generally relates to the use of metabolomics data, generated by quantization of endogenous metabolites by but not limited to mass spectrometry (MS), in particular MS-technologies such as MALDI, ESI, atmospheric pressure chemical ionization (APCI), and other methods, determination of metabolite concentrations by use of MS-technologies or alternative methods coupled to separation (LC-MS, GC-MS, CE-MS), subsequent feature selection and combination of features to classifiers including molecular data of at least two molecules.
  • MS mass spectrometry
  • MS-technologies such as MALDI, ESI, atmospheric pressure chemical ionization (APCI), and other methods
  • determination of metabolite concentrations by use of MS-technologies or alternative methods coupled to separation (LC-MS, GC-MS, CE-MS), subsequent feature selection and combination of features to classifiers including molecular data of at least two molecules.
  • concentrations of the individual markers, analytes, metabolites thus are measured and compared to reference values or data combined and processed to scores and compared to reference values thus indicating diseased states etc. with superior sensitivities and specificities compared to known procedures, clinical parameters and biomarkers.
  • analysed samples are e.g., a tissue (e.g., biopsy) sample, a blood sample, a serum sample, from a subject.
  • tissue e.g., biopsy
  • serum sample e.g., serum
  • the analytical procedure is also characterized in that a deproteinization step and/or a separation step is performed before metabolite measurement, wherein said separation step is selected from the group consisting of liquid chromatography (LC), high performance liquid chromatography (HPLC), gas chromatography, liquid-liquid-extraction (LLE).
  • LC liquid chromatography
  • HPLC high performance liquid chromatography
  • LLE liquid-liquid-extraction
  • Said deproteinization step preferably is carried out by mixing said biological sample with organic solvents such as ethanol, methanol or acetonitrile.
  • the compounds can be derivatized. They may be converted, py applying chemical methods known in the art, to the corresponding esters, amines or amides, wherein said derivatization includes: 2-Hydrazinopyridine (HP), 2-picolylamine (PA); Girard derivatization; oximation with hydroxylamine first and then silylation with hexamethyldisilazane and trifluoroacetic acid.
  • HP 2-Hydrazinopyridine
  • PA 2-picolylamine
  • Girard derivatization oximation with hydroxylamine first and then silylation with hexamethyldisilazane and trifluoroacetic acid.
  • said calibration step is carried out by
  • the step of mathematically preprocessing can be carried out e.g. by means of a statistical method on obtained raw data, particularly raw intensity data obtained by a measuring device, wherein said statistical method is selected from the group consisting of raw data obtained by mass spectrometry or mass spectrometry coupled to liquid or gas chromatography or capillary electrophoresis or by 2D gel electrophoresis, quantitative determination with RIA or determination of concentrations/amounts by quantitation of immunoblots; smoothing, baseline correction, peak picking, optionally, additional further data transformation such as taking the logarithm in order to carry out a stabilization of the variances.
  • a statistical method is selected from the group consisting of raw data obtained by mass spectrometry or mass spectrometry coupled to liquid or gas chromatography or capillary electrophoresis or by 2D gel electrophoresis, quantitative determination with RIA or determination of concentrations/amounts by quantitation of immunoblots; smoothing, baseline correction, peak picking, optionally, additional further data
  • a further step of feature selection is inserted into said preprocessing step, in order to find a lower dimensional subset of features with the highest discriminatory power between classes; and/or said feature selection is carried out by a filter and/or a wrapper approach; and/or wherein said filter approach includes rankers and/or feature subset evaluation methods; and/or wherein said wrapper approach is applied, where a classifier is used to evaluate attribute subsets.
  • said pathophysiological condition corresponds to the label " diseased” and said physiological condition corresponds to the label " healthy” or said pathophysiological condition corresponds to different labels of " grades of a disease” , “ subtypes of a disease” , different values of a “score for a defined disease” ; said prognostic condition corresponds to a label “ good” , “ medium” , “ poor” , or “ therapeutically responding” or “therapeutically non-responding” or “therapeutically poor responding”.
  • the method of the present invention is characterised in that said measuring step is carried out by high-throughput mass spectrometry.
  • said NE in infants specific endogenous compounds indicate neonatal encephalopathy, NE of affected brain area(s) and prognosis and neurological outcome due to determination of type and extent of damage of distinct brain tissues, in particular of hippocampus and / or basal ganglia in infants specific endogenous metabolites.
  • said mammalian subject is a human being
  • said biological sample is blood
  • raw data of metabolite concentrations are preprocessed using the log transformation
  • linear models are used to identify metabolites which are correlated to the extend of NE present
  • least square regression is selected as suitable supervised algorithm, and is trained with preprocessed metabolite concentrations, applying the obtained trained regression function to said pre-processed metabolite concentration data set of a subject under suspicion of having NE in infants, and using said trained regression function to diagnose or predict the extent of brain tissue-specific injury in infants.
  • the present invention allows prognosis of NE-related neurological outcome and neurological behavioural score by metabolites of the subject (with or without determination of type and extent of damage of distinct brain tissues, in particular of hippocampus and / or basal ganglia in infants specific endogenous metabolites) wherein linear models are used to identify metabolites which are differentially present; wherein linear least squares regression is selected as suitable algorithm to delineate a relationship between metabolite and extent of damage, and is trained with preprocessed metabolite concentrations, applying the obtained trained regression function to said preprocessed metabolite concentration data set of a subject under suspicion of having NE in infants, and using said trained regression to diagnose or predict the extend of brain tissue-specific injury in infants.
  • categorization of data relies on the application of (un-) supervised learning techniques.
  • Supervised learning algorithms are typically deterministic functions that map a multi-dimensional vector of biological measurements to a binary or n-ary or continuous outcome variable that encodes the absence or existence of a clinically-relevant class, phenotype, distinct physiological state or distinct state of disease or risk of developing a disease or disease treatment adequacy.
  • logistic regression (LR), (diagonal) linear or quadratic discriminant analysis (LDA, QDA, DLDA, DQDA), perceptron, shrunken centroids regularized discriminant analysis (RDA), random forests (RF), neural networks (NN), support vector machine (SVM), generalised least square regression, (non-)linear mixed-effects models, generalised (non-)linear models, mixed hidden Markov models, generalised partial least square regression (GPLS), principal component regression, partial least square regression coupled with a classification algorithm (such as LDA, K-NN or LR), projection to latent structures, partitioning around medoids (PAM), na ⁇ ve Bayes (NB), inductive logic programming (ILP), generalized additive models, gaussian processes, regularized least square regression, least absolute deviations, self organizing maps (SOM), recursive partitioning and regression trees, K-nearest neighbour classifiers (K-NN), fuzzy classifiers can be used as a standalone classif
  • the brain of the pig When comparing brain growth spurts, the brain of the pig resembles most that of the term born human baby (see Dobbing J, Sands J. Comparative aspects of the brain growth spurt. Early Hum Dev 1979 Mar;3(1):79-83 ).
  • the inhalational hypoxia model since it mimicks the human pathophysiology of a global hypoxic ischemic insult and produces spontaneous clinical and subclinical seizures, but with a high survival rate ( ⁇ 80%).
  • the encephalopathy is clinically, electrophysiologically, and neuropathologically similar to that in the asphyxiated term infant and is suitable for examining mechanisms of damage and evaluation of potential protective therapies after birth asphyxia (see Thoresen M, Haaland K, Loberg EM, Whitelaw A, Apricena F, Hanko E, et al. A piglet survival model of posthypoxic encephalopathy. Pediatr Res 1996 Nov;40(5):738-48 ).
  • the animals were bred in a piggery in Brisbane. After ventilation and detubation piglets stayed in a small animal cage with liberate access to water. Piglets were bottlefed every 3-4 hours with Survive Pig Milk Replacer (Think Pig-Country Vet Wholesaling Pty Ltd, VIC, Australia). Animals were cared for in accordance with the institution' s guidelines for experimental animals. All experiments were approved by the animal protection committee of the local authorities.
  • Piglets 9 newborn piglets were used for this study. Piglets were anaesthetized with 1-2% isofluran via a nose mask, and placed supine on a heating table to maintain body temperature around 38,5°C. An ear vein was cannulated and an induction dose of propofol (10 mg/ml, 0.5 ml/kg Diprivan 1 %, AstraZeneca Pty Ltd, NSW, Australia) was administered. Propofol (9mg/ml) and alfentanil infusion was maintained at a rate of 10 mg/kg/hr until intubation.
  • propofol 10 mg/ml, 0.5 ml/kg Diprivan 1 %, AstraZeneca Pty Ltd, NSW, Australia
  • Pulse oximeter and ECG (Marquette Tramscope 12C, Medical Systems, WI, USA) was connected as well as the amplitude-integrated EEG (BRM2; BrainZ Instruments, Auckland, NZ). piglets were intubated with an uncuffed tube and pigs were ventilated pressure-controlled with an SLE Newborn 250 (Surrey, UK). Anesthesia was reduced to 10 mg/kg/hr until the end of HI. An additional peripheral venous line was inserted for continuous 10% dextrose infusion at a rate of 3 ml/kg/hr and antibiotics (cephalotin 20 mg/kg and gentamicine 2.5 mg/kg). An umbilical artery was inserted for continuous blood pressure monitoring and blood gas analysis. Blood gasses were collected before HI, every 10 minutes during HI until 60 min after HI.
  • blood samples were taken at the following time points: 30 min after asphyxia and 21 hours after resuscitation.
  • Brain injury was assessed with the aEEG for both EEG pattern and epileptic activity, with a clinical neurological score, by histology (haematoxylin and eosin staining) using a previously described rating system (see Lorek A, Takei Y, Cady EB, Wyatt JS, Penrice J, Edwards AD, et al. Delayed ("secondary") cerebral energy failure after acute hypoxiaischemia in the newborn piglet: continuous 48-hour studies by phosphorus magnetic resonance spectroscopy. Pediatr Res 1994 Dec;36(6):699-706 ) and for caspase-3 activity in 4 cortical areas, thalamus, basal ganglia and hippocampus. Thereby the hippocampus and basal ganglia are of outmost interest.
  • Caspase 3-activity was determined at 48h after HI in all other brain regions, including 4 cortical areas, basal ganglia and hippocampus.
  • Histology was performed using the earlier described score in each brain region. Also a total histology score was calculated for each treatment group, summing all the individual histology scores.
  • a neurobehavioral score was assessed at least at 4 hourly time points in the first 24h and at 48h. This score contains 9 items of maximal 2 points, so the maximal score is 18 points.
  • the nine neurologic items were scored as: 2, normal; 1 , moderately abnormal; or 0, definitely pathologic. Neurologic items were: 1 ) Normal respiration, without apnea, retractions, or need for oxygen; 2 ) consciousness; 3 ) orientation.
  • Plasma samples were prepared by standard procedures and stored at (-75°C). To enable analysis of all samples simultaneously within one batch, samples were thawed on ice (1 h) on the day of analysis and centrifuged at 18000g at 2°C for 5 min. All tubes were prepared with 0.001 % BHT (butylated hydroxytoluene; Sigma-Aldrich, Vienna, Austria) to prevent autoxidation.
  • BHT butylated hydroxytoluene
  • the LC-MS/MS system consisted of an API 5000TM triple quadrupole mass spectrometer (AB Sciex) equipped with a Turbo VTM ESI source and an Agilent 1200 HPLC system (Agilent Technologies). Chromatographic separation was performed using an Agilent Zorbax Eclipse XDB C18 column (100 x 3.0 mm, 3.5 ⁇ m) with guard column (C 18, 4 x 2 mm in Security Guard Cartridge, Phenomenex). AnalystTM software (version 1.4.2, Applied Biosystems) was used for data acquisition and processing. For comprehensive statistical analysis the data were exported.
  • the ESI source was operated in negative ion mode and an ion-spray voltage of -3 kV was applied. Heater temperature was set at 400 °C.
  • the AbsoluteIDQ kit p150 (Biocrates Life Sciences AG, Innsbruck, Austria) was prepared as described in the manufacturer' s protocol. In brief, 10 ⁇ L of plasma was added to the center of the filter on the upper 96-well kit plate and was dried using a nitrogen evaporator (VLM Laboratories, Bielefeld, Germany). Subsequently, 20 ⁇ L of a 5% solution of phenyl-isothiocyanate was added for derivatization. After incubation, the filter spots were dried again using an evaporator.
  • the metabolites were extracted using 300 ⁇ L of a 5 mM ammonium acetate solution in methanol.
  • the extracts were obtained by centrifugation into the lower 96-deep well plate, followed by a dilution step with 600 ⁇ L of kit MS running solvent.
  • Mass spectrometric analysis was performed on an API4000 Qtrap® tandem mass spectrometry instrument (Applied Biosystems/MDS Analytical Technologies, Foster City, CA) equipped with an electro-spray ionization (ESI)-source, using the analysis acquisition method as provided in the AbsoluteIDQ kit.
  • the standard FIA-MS/MS method was applied for all measurements with two subsequent 20- ⁇ L injections (one for positive and one for negative mode analysis).
  • MRM detection was used for quantification, applying the spectra parsing algorithm integrated into the MetIQ software (Biocrates Life Sciences AG, Innsbruck, Austria).
  • MetIQ software Biocrates Life Sciences AG, Innsbruck, Austria.
  • concentrations for 148 metabolites all analytes were determined with the metabolomics kit except for the amino acids, which were determined by a different method) obtained by internal calibration were exported for comprehensive statistical analysis.
  • Amino acids and biogenic amines were quantitatively analyzed by reversed phase LC-MS/MS to obtain the chromatographic separation of isobaric (same MRM ion pairs) metabolites for individual quantification performed by external calibration and by use of internal standards.
  • a 10 ⁇ L sample volume is required for the analysis using the following sample preparation procedure. Samples were added on filter spots placed in a 96- solvinert well plate (internal standards were placed and dried down under nitrogen before), fixed above a 96 deep well plate (capture plate). 20 ⁇ L of 5% phenyl-isothiocyanate derivatization reagent was added. The derivative samples were extracted after incubation by aqueous methanol into the capture plate.
  • Oxysterols were quantitatively analyzed by reversed phase LC-ESI-MS/MS to realize liquid chromatographic separation and thus individual quantification of isobaric oxysterols.
  • the most selective detection was performed in positive MRM detection mode using a 4000 Qtrap® tandem mass spectrometry instrument (Applied Biosystems/MDS Analytical Technologies, Foster City, CA). Data were quantified with Analyst 1.4.2 software (Applied Biosystems, Foster City, CA). Ratios of external to internal standards were applied for quantification by means of external 6-point calibration. A sample volume of 20 ⁇ L (plasma) was necessary for the analysis.
  • the sample preparation included: I) protein precipitation by placing a 20 ⁇ L sample volume on the filter spot, and precipitation by 200 ⁇ L Na ⁇ ve; II) hydrolysis by 100 ⁇ L of 0.35 M KOH in 95% ethanol for 2 hrs; III) a washing step (3x200 ⁇ L H 2 O) to remove hydrolysis reagent; and, finally, IV) extraction by means of 100 ⁇ L aqueous methanol.
  • the 20 ⁇ L sample extracts were analyzed by the developed LC-ESI-MS/MS method.
  • HILIC hydrophilic interaction liquid chromatography
  • a hydrophilic interaction liquid chromatography (HILIC)-ESI-MS/MS method in a highly selective negative MRM detection mode was used.
  • the MRM detection was performed using an API4000 QTrap® tandem mass spectrometry instrument (Applied Biosystems/MDS Analytical Technologies, Foster City, CA).
  • a 20 ⁇ L sample volume (plasma) was proteinprecipitated and simultaneously extracted with aqueous methanol in a 96-well plate format. Internal standards (ratio external to internal standard) and external calibration were used for highly accurate quantification. Data were quantified with Analyst 1.4.2 software (Applied Biosystems, Foster City, CA) and finally exported for statistical analysis.
  • Parsimonious multi-metabolite panels can be used for predicting each outcome described in the present invention rather than individual metabolite marker.
  • Approach to search for marker composites is done using a population-based incremental learning algorithm using all 101 metabolites.
  • regression coefficient i.e. marker weights in the model
  • Predictive power of the model is assessed by leave one out cross-validation.
  • model accuracy is defined as the correlation coefficient between the original (or true) values of the predictand and their predicted values by resampling.
  • Neonatal encephalopathy was associated with major changes in the plasma metabolome.
  • intermediates which correlated alone or in combination with the extent of brain injury in the hippocampus, basal ganglia and the neurological score.
  • Example 1 Hypoxia-induced damage of hippocampus
  • Prob designates the actual probability (in %) to enter a combination of metabolites.
  • Table 5 Outcome parameter: Brain damage in hippocampus Short Full name Cor Pvalue Rsq Prob 1 Lac Lactate 0,870 0,002 75,69 61,38 2 Fum Fumaric acid 0,753 0,019 56,63 43,45 3 Ac-Orn N-acetylornithine 0,747 0,021 55,73 40,69 4 Carnosine Carnosine -0,741 0,022 54,96 27,59 5 C5:1-DC Glutaconylcarnitine / Mesaconylcarnitine (Undecanoylcarnitine) 0,666 0,050 44,35 20,00 6 C16:2 Hexadecadienoylcarnitine 0,464 0,208 21,53 16,55 7 Pent-P Pentosephosphate (e.g.
  • Figure 1 a illustrates the predictive abilities of the combination of metabolites based on a lead metabolite correlating with the extent of brain damage in the hippocampus.
  • the box-and-whisker diagrams represent the distribution of the cross-validated correlation coefficient (y-axis) for combinations comprising a lead metabolite (x-axis) and up to 6 metabolites from the initial dataset.
  • Figure 1b illustrates the predictive abilities (i.e. accuracy) of all adequate metabolite combinations correlating with the extent of brain damage in the hippocampus.
  • the box-and-whisker diagrams represent the distribution of the cross-validated correlation coefficient (y-axis) for combinations of 2 to 6 (x-axis) metabolites.
  • Figure 1c illustrates the probabilities of single metabolites to enter a combination of metabolites correlating with cell death in the hippocampus. Probabilities are calculated over all models presented in Figure 1 b. Metabolites are sorted according to their likelihood to be included in a model and graphed back-to-back depending of their respective (i.e. positive or negative) contributions to the regression models. Left: metabolites inducing less damage in the hippocampus. Right: metabolites inducing more damage in the hippocampus.
  • Example 2 Hypoxia-induced damage of basal ganglia
  • Prob designates the actual probability (in %) to enter a combination of metabolites.
  • Table 6 Outcome parameter: Brain damage in Basal ganglia Short Full name Cor Value Rsq Prob 1 Met Methionine 0,821 0,007 67,41 20,79 2 SM (OH) C22:2 Hydroxysphingomyelin with acyl residue sum C22:2 -0,840 0,005 70,54 19,19 3 SM (OH) C14:1 Hydroxysphingomyelin with acyl residue sum C14:1 -0,770 0,015 59,36 19,06 4 Met-SO Methionine-Sulfoxide 0,774 0,014 59,97 18,63 5 SM C16:1 sphingomyelin with acyl residue sum C16:1 -0,772 0,015 59,52 17,67 6 SM (OH) C22:1 Hydroxysphingomyelin with acyl residue sum C22:1 -0,768 0,016
  • Ribose-5-phosphate + Ribulose-5-phosphate) 0,514 0,157 26,44 1,14 50 total DMA Total dimethylarginine 0,546 0,128 29,80 1,12 51 Creatinine Creatinine -0,199 0,607 3,97 1,04
  • Figure 2a illustrates the predictive abilities of combinations of metabolites based on a lead metabolite correlating with the extent of brain damage in the basal ganglia.
  • the box-and-whisker diagrams represent the distribution of the cross-validated correlation coefficient (y-axis) for combinations comprising a lead metabolite (x-axis) and up to 7 metabolites from the initial dataset.
  • Figure 2b illustrates the predictive abilities (i.e. accuracy) of all adequate metabolite combinations correlating with the extent of brain damage in the basal ganglia.
  • the box-and-whisker diagrams represent the distribution of the cross-validated correlation coefficient (y-axis) for combinations of 2 to 7 (x-axis) metabolites.
  • Figure 2c illustrates the probabilities of single metabolites to enter a combination of metabolites correlating with the extent of brain damage in the basal ganglia. Probabilities are calculated over all models presented in Figure 2b . Metabolites are sorted according to their likelihood to be included in a model and graphed back-to-back depending of their respective (i.e. positive or negative) contributions to the regression models. Left: metabolites inducing less damage in the basal ganglia. Right: metabolites inducing more damage in the basal ganglia.
  • Prob designates the actual probability (in %) to enter a combination of metabolites.
  • Figure 3a illustrates the predictive abilities of the combination of metabolites based on a lead metabolite correlating with the extent of brain injury as described by the neurological score at 48h.
  • the box-and-whisker diagrams represent the distribution of the cross-validated correlation coefficient (y-axis) for combinations comprising a lead metabolite (x-axis) and up to 6 metabolites from the initial dataset.
  • Figure 3b illustrates the predictive abilities (i.e. accuracy) of all adequate metabolite combinations correlating with the extent of brain injury as described by the neurological score at 48h.
  • the box-and-whisker diagrams represent the distribution of the cross-validated correlation coefficient (y-axis) for combinations of 2 to 6 (x-axis) metabolites.
  • Figure 3c illustrates the probabilities of single metabolites to enter a combination of metabolites correlating with the extent of brain injury as described by the neurological score at 48h. Probabilities are calculated over all models presented in Figure 3b . Metabolites are sorted according to their likelihood to be included in a model and graphed back-to-back depending of their respective (i.e. positive or negative) contributions to the regression models. Left: metabolites worsening the neurological outcome. Right: metabolites improving the neurological outcome.

Abstract

The invention generally relates to the identification metabolites and signatures (panels) of metabolites, which are applicable as biomarkers in clinical diagnosis, in particular for neonatal encephalopathy. They are useful tools in differential clinical diagnosis for early detection of brain injury, determination of brain areas affected by the insults and prediction of adverse neurological outcome and may also be applied in diagnosing disease progression and treatment effect. The present invention more particularly relates to an in vitro method for predicting the likelihood of neonatal encephalopathy of distinct brain areas, identification of affected brain area(s) of neonatal encephalopathy and risk of brain damage and prognosis and neurological outcome due to identification of the type and extent of damage of distinct brain tissues, in particular of hippocampus and / or basal ganglia.

Description

  • The invention generally relates to the identification of metabolites and signatures (panels) of metabolites, which are applicable as biomarkers in clinical diagnosis, in particular for neonatal encephalopathy. They are useful tools in differential clinical diagnosis for early detection of brain tissues affected by brain damage and may also be applied in diagnosing disease progression and determination of affected brain areas and determination of associated adverse neurological outcome.
  • The present invention more particularly relates to an in vitro method for predicting the likelihood of neonatal encephalopathy of distinct brain areas, identification of affected brain area(s) of neonatal encephalopathy and risk of brain damage and prognosis and neurological outcome due to identification of the type and extent of damage of distinct brain tissues, in particular of hippocampus and / or basal ganglia.
  • Background of the Invention
  • Neonatal encephalopathy (NE) is a serious condition with life long consequences. NE is the most important cause of morbidity and mortality in the term born baby. About 10% of those affected die and 25% are severely handicapped due to long-term complications such as cerebral palsy, mental retardation with learning difficulties, cerebral visual impairments and/or epilepsy. Its long-term consequences impose a large burden on the child and family and on worldwide healthcare budgets. The estimated costs of the treatment of sequelae of NE in the US is around 750 000 US $ per patient. One major reason for NE is pre-, peri- and postnatal asphyxia, a condition in which the fetus or newborn lacks oxygen. In the Western world about 0.9% of newborns, about 130.000 in the developed world and 30.000 in European Union suffer from a moderate to severe form of perinatal asphyxia. However NE could not always be explained by moderate to severe asphyxia and the cause of NE often could not be identified. It has been shown that foetuses/newborns with rather mild asphyxia, who initially seem to recover without complications, will have behavioural problems in childhood, which can be traced back to the perinatal insult.
  • A study published in Lancet suggests that the definition of NE does not include all patients with long-term neurological outcome after resuscitation (Odd DE, Lewis G, Whitelaw A, Gunnell D.Lancet. 2009 May 9;373(9675):1615-22). Resuscitated infants asymptomatic for the " classically defined" encephalopathy, however, undergoing actual brain damage (or prone to actual brain damage) might result in a larger proportion of adults with low IQs than do those who develop neurological symptoms consistent with encephalopathy. Based on this publication 40% of cases with long-term adverse neurological outcome are missed by current, state of the art, diagnostic means. Thus, in summary neonatal encephalopathy and its long-lasting consequences is a huge burden to the child, to its family. Consequently, there is a lack of early markers identifying newborns at risk for NE.
  • Till date, therapy was limited to supportive care including adequate oxygenation and restoring of circulation by appropriate, rapid and effective resuscitation. It is vital to maintain adequate ventilation, systemic blood pressure, tissue perfusion, and normoglycaemia, to control seizures, and to correct electrolyte and acid-base disorders. However, in the past few years hypothermia (whole body hypothermia or selective head cooling), has been introduced to reduce morbidity and mortality following perinatal asphyxia in term born neonates. In a recent meta-analysis combining the results of 1320 neonates the effect of moderate hypothermia was found to be associated with a moderate reduction in death and neurological impairment at 18 months. It is of outmost importance that the therapeutic benefit of hypothermia is strongly dependent on the time point of its initiation. The earlier the diagnosis is made and the early therapy can be started the more neuroprotection can be achieved. Accordingly, early detection of neonatal encephalopathy and severity assessment is vital to therapeutic success.
  • Current diagnostic tests to evaluate whether a newborn is at risk to develop neurological sequelae have major limitations with low sensitivity and specificity. The diagnostic criteria for neonatal encephalopathy in term newborn infants require i) signs of perinatal and postnatal asphyxia, abnormal blood gas values (increase in base deficit, blood lactate values, low cord pH in the umbilical artery (UApH) and need for resuscitation, and ii) signs of brain involvement and abnormal neurology characterized by neurological scores (Sarnat or Thompson score) and any presence of seizure activity and iii) demonstrating electroencephalographic evidence of abnormal cerebral function by means of the amplitude-integrated or ten-lead standard EEG. These established tests, however, have major limitations. We have recently shown that that so called " abnormal blood gas values" do not correlate with the extent of hypoxia. This is reflected by low sensitivity and specificity for NE [Groenendaal, de Vroes Semin Neonatol 2000, ]. The most precise test currently established is the use of amplitude integrated EEG (aEEG) with a sensitivity and specificity of 80% in the first 6 hours of life. The use of aEEG is challenged by its availability, required expertise and timing. It is not available in all children' s hospitals and in none of the delivery units. Thus the diagnosis by aEEG can only be made after transfer into a children' s clinic in which the tool and the medical expertise is available. In addition the process of implementation of the aEEG and the evaluation of the signal takes at least 30 to 45 minutes. This is of particular importance since it is known that treatment is more effective the earlier it is initiated. Imaging technologies such as MRT (Magnetic Resonance Tomography), however, are applicable from day three after birth only and therefore, are not useful for early diagnosis and timely therapy.
  • Currently used diagnostic methods thus require time and appropriate equipment with high costs, do not recognize affected parts of the brain along with individual prognosis, afford results too late for appropriate therapy and with frequently unsatisfying sensitivities. These available diagnostic means, therefore, have major limitations such as reduced area under the curve (AUC) and/or delay of diagnosis or increased costs due to equipment required. Accordingly, these procedures also do not allow a timely assessment of an acute and rapidly evolving disease nor a differentiation of brain areas affected by hypoxia. Overall the situation is far from satisfying and from providing a rapid, reliable and precise diagnosis of brain damage in neonates, let alone a differentiation of affected brain areas or tissues, a prerequisite, however, for selection and initiation of appropriate therapy; there is still an urgent need for differentiation of brain injury from any other state of health to enable timely and adequate treatment.
  • Due to these limitations academic research groups have been looking for potential alternative biomarkers of NE like interleukin-1b, 6,8, 9, 12, NSE, S100, CK-BB, Phosphorylated axonal neurofilament heavy chain (pNF-H protein2) Ubiquitin C-terminal hydrolase 1 (UCHL1 protein) (Ramaswamy et al. (2009) Pediatr Neurol, ). However, although these markers have been published, none of these were finally developed to a diagnostic product because of major limitations. The studies are not uniform and show a significant amount of heterogeneity with a tremendous variation in the assessment of outcomes and variation in inclusion criteria. Most frequently the inclusion of patients was based on " established" tests. Thus most of the studies confirm the diagnosis of the established tests and were most precise for infants with severe injury who are already easily identified and do not provide any additional information. Most of the studies had small sample size, so it is not possible to calculate true predictive value for all of the mentioned biomarkers and no attempt has been made to correlate concentrations of these marker candidates with brain areas affected by NE. In addition, correlation is strongest at times well after the latent phase, which is way too late for early and therefore, effective treatment.
  • In summary there is no single precise biomarker available to diagnose or predict neonatal encephalopathy in newborns at an early stage e.g. immediately after birth or any biomarker which provides information on brain areas affected by damaging conditions. Lesions detectable on a biochemical level only such as by using endogenous metabolites as biomarkers and not monitorable by alternate means, however, can be used to assess neurological outcome which is of outstanding value for clinical diagnosis.
  • In classical patient screening and diagnosis, the medical practitioner uses a number of diagnostic tools for diagnosing a patient suffering from a certain disease. Among these tools, measurement of a series of single routine parameters, e.g. in a blood sample, is a common diagnostic laboratory approach. These single parameters comprise for example enzyme activities and enzyme concentration and/or enzyme detection
  • As far as such diseases are concerned, which easily and unambiguously can be correlated with one single parameter or a few number of parameters achieved by clinical chemistry, these parameters have proved to be indispensable tools in modern laboratory medicine and diagnosis. However, in complex pathophysiological conditions, for which an unambiguously assignable single parameter or marker is not available, differential diagnosis from blood or tissue samples is currently difficult to impossible.
  • Only recently metabolomic analyses for specific diagnostic approaches were described in the prior art:
    • According to WO 2011/012553 A1 a method for predicting the likelihood of an onset of an inflammation associated organ failure is provided, which is based on quantitative metabolomics analysis of a biological sample of a mammalian subject in vitro. In particular, the concentration of acylcarnitines, sphingomyelins, hexoses and glycerophospholipids in plasma by means of FIA-MS/MS is determined. Furthermore, amino acids and biogenic amines were analyzed by reversed phase LC-MS/MS in plasma. Prostanoids - a term summarizing prostaglandins (PG), thromboxanes (TX) and prostacylines - and oxidised fatty acid metabolites in plasma extracts were analysed by LC-ESI-MS/MS and in brain homogenate extracts by online solid phase extraction (SPE)-LC-MS/MS. Furthermore, energy metabolism (organic acids) was analyzed by LC-MS/MS. For the quantitative analysis of energy metabolism intermediates (glycolysis, citrate cycle, pentose phosphate pathway, urea cycle) hydrophilic interaction liquid chromatography (HILIC)-ESI-MS/MS method was applied.
  • WO 2010/128054 A1 , corresponding to EP 2 249 161 A1 , describes a method of diagnosing asphyxia. In particular, said document refers to a method for in vitro diagnosing e.g. perinatal asphyxia and disorders related to hypoxia, characterized by quantitatively detecting in at least one biological sample of at least one tissue of a mammalian subject a plurality of asphyxia specific compounds having a molecular weight of less than 1500 Dalton, except lactate, comprising the steps of:
    1. a) selecting said compounds;
    2. b) measuring at least one of the parameters selected from the group consisting of: concentration, level or amount of each individual metabolite of said plurality of metabolites in said sample, qualitative and/or quantitative molecular pattern and/or molecular signature; and using and storing the obtained set of values in a database;
    3. c) calibrating said values by comparing asphyxia-positive and/or asphyxia-negative reference parameters;
    4. d) comparing said measured values in the sample with the calibrated values, in order to assess whether the patient is asphyxia-positive or asphyxia-negative.
  • The method according to WO 2010/128054 A1 uses asphyxia specific compounds as biomarkers which are endogenous compounds being selected from the group consisting of: biogenic amines; carnitine-derived compounds; amino acids; bile acids; carboxylic acids; eicosanoids; lipids; precursors of cholesterol, cholesterol metabolites, prostanoids; and sugars. Furthermore, WO 2010/128054 A1 relates to a method of in vitro estimating duration of hypoxia in a patient, a method for in vitro monitoring of normoxic, hypoxic and hyperoxic conditions and/or normobaric and hyperbaric oxygen therapy and a kit for carrying out the methods thereof.
  • However, neither assignment of metabolite concentrations to total brain damage or NE nor to distinct brain regions nor neurological outcome in neonates is addressed with the metabolomic studies disclosed in WO 2011/012553 A1 and WO 2010/ 128054 A1 .
  • Solberg R and colleagues (" Metabolomic Analyses of Plasma Reveals New Insights into Asphyxia and Resuscitation in Pigs" , PLoS ONE, 2010, 5(3)) disclose detection of a number of metabolites in plasma taken before and after hypoxia as well as after resuscitation, in asphyxiated piglets, in order to evaluate pathophysiological mechanisms of hypoxemia in newborns. Hypoxemia of different durations was induced in newborn piglets before randomization for resuscitation with 21 % or 100% oxygen for 15 min in order to detect markers of the duration/severity of hypoxia and to detect markers of therapy response due to different resuscitation protocols. The metabolites of the study of Solberg et al. includes amino acids, particularly branched chained amino acids, metabolites of the Krebs cycle, including alpha-ketoglutarate, succinate and fumarate, biogenic amines, bile acids, prostaglandins, sphingolipids, glycerophospholipids, oxysterols and acylcarnitines. Assessment of brain injuries per se, or biomarkers to detect brain injuries per se are not comprised by the Solberg et al. paper (cf. page 9, left column, lines 2-3), and identification or differentiation of brain areas or tissues or assessment of neurological outcome is not addressed.
  • Beckstrom et al. ( J ChromatogrA, 2011 Vol 1218, 1899-1906) evaluated whether metabolomic profiling can reveal metabolite changes in plasma after asphyxia in a Macaca nemestrina model of perinatal asphyxia. The metabolic profile of post-asphyxia samples showed marked variability compared to the pre-asphyxia samples. This metabolomic analysis confirmed lactate and creatinine as markers of asphyxia and discovered new metabolites including succinic acid and malate (intermediates in the Krebs cycle) and arachidonic acid (a brain fatty acid and inflammatory marker). Although these metabolite changes reflect the changes of asphyxia (similarly to the publication of Solberg et.al.), the metabolite changes were not related to brain injury, to identification or differentiation of brain areas or tissues or assessment of neurological outcome.
  • Chu, C.Y et al.(Clinical Biochemistry, 2006, Vol 39, 203-209) describe metabolomic and bioinformatic analyses in asphyxiated neonates. In particular they analyzed urine of such neonates and defined eight urinary organic acids which were significantly associated with the prognosis of neurodevelopmental handicap with high sensitivity and specificity. They further divided said acids into two classes of acids, one consisting of acids which were associated with good neonatal outcome (ethylmalonate, 3-hydroxy-3-methylglutarate, 2-hydroxyglutarate, 2-oxogluturate) and the other with poor outcome (glutarate, methylmalonate, 3-hydroxybutyrate, orotate). No blood samples were analyzed; nor were said urinary metabolites or combinations thereof correlated to brain injury, injured areas of the brain or any neurological behaviour scoring. However all of these metabolites we determined only in urine samples, and, moreover, not within the first hours of life.
  • Finally, Mueller et. al. (" Mass Spectrometric Quantifications of Organic Acids and Acylcarnitines in Early Random Urine Specimens of Newborns with Perinatal Complications: Feasability Study for the Prediction of the Neuro-Developmental Outcome" , The Internet Journal of Pediatrics and Neonatology, 20077(2)) describe the use of mass spectrometric quantifications of organic acids and acylcarnitines for the prediction of the neuro-developmental outcome in newborns with perinatal complications. This group investigated a number of 65 quantitatively determined metabolites (42 organic acids, 22 acylcarnitines, free carnitine and 15 ratios) in urine of infants within the first 72 hours of life of infants. Reliable prediction for development of NE caused by severe asphyxia was demonstrated with metabolite monitoring of the lactic acid/creatinine ratio in urine of asphyxiated newborns. However, an unexpected result of the Mueller et al. study was the finding that the total amount of urinary acylcarnitines did not significantly differ between the comparison group and the patient group with severe neurological defects. Blood metabolite concentration changes related to brain injury, to identification or differentiation of brain areas or tissues, or assessment of neurological outcome were not described. Mutter et al. observed a limited number of metabolic carboxylic acid combinations for predicting the neurological outcome of preterm and term newborns at the end of the first year of life. Said metabolite combinations comprise lactic acid in combination with one or more of 3-hydroxybutyric acid, 3-hydroxyisovaleric acid, methylmalonic acid, 4-hydroxyphenyllactic acid, and 5-oxoproline. Again, all of these metabolites we determined only in urine samples, and, moreover, not within the first hours of life.
  • In summary so far no metabolic markers or marker signatures have been identified for indicating and diagnosing NE at a time point as early as possible (defined as within the first 6 hours after the insult) in infants. No teaching is found in the prior art suggesting that there might exist markers applicable to the identification of neonatal encephalopathy and / or differentiation of brain tissues altered by hypoxic conditions. Solely a couple of intermediates, possibly involved in pathobiochemistry, have been discussed in the wider context of brain damage and chemical mediators that may contribute to gray matter injury.
  • Thus, the problem underlying the present invention is to provide an early diagnostic approach for assessing NE in infants with high sensitivities and specificities, capable of determining brain tissues involved and/or brain tissues damaged and/or prone to subsequent future damage and/or predict neurological outcome.
  • Summary of the invention
  • Given the remarkable and rapid potential of NE in infants to progress into an irreversible and/or life-threatening condition, the current situation is highly problematic and unsatisfying. An early and reliable multi-parameter diagnosis in small sample sizes for identification of patients with potential NE, identification of respective brain tissues affected and / or adverse neurological outcome is highly valuable since treatment (induced therapeutic hypothermia) is available and its efficiency increases the earlier the therapy is initiated. Early diagnosis as defined here includes diagnosis within the first 6 hours after birth and the therapeutic time window to start hypothermia is 6 hours.
  • The above mentioned problems are solved by the embodiments as defined in the attached claims.
  • As will be explained in more detail below, the present invention relates to markers of NE, in particular of brain injury and neurological behavioural outcome in infants, its severity and distribution (affected brain areas). In particular embodiments, the present invention provides metabolites that are differentially present in infants affected by NE. The present invention also identifies a series of metabolites (or signatures of metabolites) as being differentially present in subjects depending on the severity of brain injury in basal ganglia, hippocampus or other distinct brain tissues and neurological outcome.
  • The present invention thus provides a solution to the aforementioned diagnostic problems based on the application of a new technology in this context and on previously unknown lists of endogenous metabolites as diagnostic marker for the identification NE and of affected brain tissues. Since metabolite concentration differences in biological fluids and tissues provide links to the various phenotypical responses, metabolites are suitable biomarker candidates.
  • The present invention allows for an early accurate, rapid, and sensitive prediction and diagnosis of NE in infants with an assignment of damage to distinct brain tissues and assessment of neurological outcome, in particular but not limited to hippocampus and basal ganglia through a measurement of a plurality (2 or more) of endogenous metabolic biomarker (metabolites) taken from a biological sample at a single point in time.
  • This is accomplished by obtaining a biomarker panel at a single point in time from an individual, particularly an individual at risk of developing brain injury, infants having brain injury, or suspected of having brain injury, and comparing the biomarker profile from the individual to reference biomarker values or scores. The reference biomarker values may be obtained from a population of individuals (a "reference population") who are, for example, afflicted with brain injury assigned to affected brain tissues, in particular hippocampus und basal ganglia, or who are suffering from brain injury assignable to distinct brain tissues or a particular stage in the progression of brain injury. If the biomarker panel values or score from the individual contains appropriately characteristic features of the biomarker values or scores from the reference population, then the individual is diagnosed as being likely of having or developing brain injury assignable but not limited to damage of hippocampus and or basal ganglia brain tissues, as being afflicted with brain injury attributable but not limited to damage of hippocampus and/or basal ganglia brain tissues allowing also an assessment of neurological outcome.
  • Brief description of the drawings
    • Figure 1a illustrates the predictive abilities (i.e. accuracy) of the combination of metabolites based on a lead metabolite correlating with the extent of brain damage in the hippocampus. The box-and-whisker diagrams represent the distribution of the cross-validated correlation coefficient (y-axis) for combinations comprising a lead metabolite (x-axis) and up to 6 metabolites from the initial dataset.
    • Figure 1b illustrates the predictive abilities (i.e. accuracy) of all adequate metabolite combinations correlating with the extent of brain damage in the hippocampus. The box-and-whisker diagrams represent the distribution of the cross-validated correlation coefficient (y-axis) for combinations of 2 to 6 (x-axis) metabolites.
    • Figure 1c illustrates the probabilities of single metabolites to enter a combination of metabolites correlating with the extent of brain injury in the hippocampus. Probabilities are calculated over all models presented in Figure 1 b. Metabolites are sorted according to their likelihood to be included in a model and graphed back-to-back depending of their respective (i.e. positive or negative) contributions to the regression models. Left: metabolites inducing less damage in the hippocampus. Right: metabolites inducing more damage in the hippocampus.
    • Figure 2a illustrates the predictive abilities (i.e. accuracy) of the combination of metabolites based on a lead metabolite correlating with the extent of brain damage in the basal ganglia. The box-and-whisker diagrams represent the distribution of the cross-validated correlation coefficient (y-axis) for combinations comprising a lead metabolite (x-axis) and up to 6 metabolites from the initial dataset.
    • Figure 2b illustrates the predictive abilities (i.e. accuracy) of all adequate metabolite combinations correlating with the extent of brain damage in the basal ganglia. The box-and-whisker diagrams represent the distribution of the cross-validated correlation coefficient (y-axis) for combinations of 2 to 7 (x-axis) metabolites.
    • Figure 2c illustrates the probabilities of single metabolites to enter a combination of metabolites correlating with the extent of brain injury in the basal ganglia. Probabilities are calculated over all models presented in Figure 2b. Metabolites are sorted according to their likelihood to be included in a model and graphed back-to-back depending of their respective (i.e. positive or negative) contributions to the regression models. Left: metabolites inducing less damage in the basal ganglia. Right: metabolites inducing more damage in the basal ganglia.
    • Figure 3a illustrates the predictive abilities (i.e. accuracy) of the combination of metabolites based on a lead metabolite correlating with the extent of brain injury as described by the neurological score at 48h. The box-and-whisker diagrams represent the distribution of the cross-validated correlation coefficient (y-axis) for combinations comprising a lead metabolite (x-axis) and up to 7 metabolites from the initial dataset.
    • Figure 3b illustrates the predictive abilities (i.e. accuracy) of all adequate metabolite combinations correlating with the extent of brain injury as described by the neurological score at 48h. The box-and-whisker diagrams represent the distribution of the cross-validated correlation coefficient (y-axis) for combinations of 2 to 6 (x-axis) metabolites.
    • Figure 3c illustrates the probabilities of single metabolites to enter a combination of metabolites correlating with the extent of brain injury as described by the neurological score at 48h. Probabilities are calculated over all models presented in Figure 3b. Metabolites are sorted according to their likelihood to be included in a model and graphed back-to-back depending of their respective (i.e. positive or negative) contributions to the regression models. Left: metabolites worsening the neurological outcome. Right: metabolites improving the neurological outcome.
    Detailed description of the invention a) Definitions
  • " Neonatal encephalopathy" (or NE) in the context of the present invention is defined as disturbed neurological function in the earliest days of life in the newborn infant resulting in long-term adverse neurological, psychological and neurobehavioral adverse outcome. NE can result from a wide variety of conditions and often remains unexplained. Given that the underlying nature of brain injury causing neurologic impairment in a newborn is often poorly understood, NE has emerged as the preferred terminology to describe central nervous system dysfunction in the newborn period, as it does not imply a specific underlying pathophysiology.
  • " Brain injury" or " brain damage" in the context of the present invention is defined as the occurrence of increased cell death by apoptosis and necrosis in any brain area of any cell type and abnormal neuronal function and network compared to healthy controls. Brain injury is assessed with the aEEG for both EEG pattern and epileptic activity, with a clinical neurological score, by histology (haematoxylin and eosin staining) and for caspase-3 activity in 4 cortical areas.
  • Unless otherwise stated the short names of chemical compounds as used herein shall have the following meanings which can be taken from subsequent Table 1: Table 1: Short names of chemical compounds (metabolites or metabolic markers) as analysed in the context of the present invention
    Short Name Common name Chemical class Chemical class short Potential CAS-Number
    alpha-KGA alpha-Ketoglutaric acid dicarboxylic acids En.Met 328-50-7
    Fum Fumaric acid dicarboxylic acids En.Met 110-17-8;110-16-7
    Hex-P Hexosephosphate (e.g. Glucose-1-phosphate + Glucose-6-phosphate + Fructose-6-phosphate) sugars En.Met 56-73-5;643-13-0;59-56-3;3672-15-9;2255-14-3;27251-84-9;55607-88-0;15978-08-2;53798-20-2;19046-69-6;2255-14-3
    Lac Lactate sugars En.Met 79-33-4;10326-41-7;503-66-2;50-21-5
    Pent-P Pentosephosphate (e.g. Ribose-5-phosphate + Ribulose-5-phosphate) sugars En.Met 3615-55-2;4300-28-1;4151-19-3;14075-00-4;13137-52-5
    OAA Pyruvate + Oxaloacetate carboxylic acids En.Met 328-42-7
    Suc Succinic acid dicarboxylic acids En.Met 110-15-6
    C0 Carnitine (free) acylcarnitines Ac.Ca. 541-14-0;541-15-1;406-76-8
    C10 Decanoylcamitine [Caprylcarnitine] (Fumarylcarnitine) acylcarnitines Ac.Ca. 1492-27-9
    C10:2 Decadienoylcarnitine acylcarnitines Ac.Ca.
    C12 Dodecanoylcarnitine [Laurylcarnitine] acylcarnitines Ac.Ca. 25518-54-1
    C14:1 Tetradecenoylcarnitine [Myristoleylcarnitine] acylcarnitines Ac.Ca. 835598-21-5
    C14:1-OH 3-Hydroxytetradecenoylcarnitine [3-Hydroxymyristoleylcarnitine] acylcarnitines Ac.Ca.
    C14:2 Tetradecadienoylcarnitine acylcarnitines Ac.Ca.
    C14:2-OH 3-Hydroxytetradecadienoylcarnitine acylcarnitines Ac.Ca.
    C16 Hexadecanoylcarnitine [Palmitoylcarnitine] acylcarnitines Ac.Ca. 1935-18-8;2364-66-1;2364-67-2
    C16:2 Hexadecadienoylcarnitine acylcarnitines Ac.Ca.
    C18 Octadecanoylcarnitine [Stearylcarnitine] acylcarnitines Ac.Ca. 1976-27-8
    C18:1 Octadecenoylcarnitine [Oleylcarnitine] acylcarnitines Ac.Ca. 13962-05-5
    C18:1-OH 3-Hydroxyoctadecenoylcarniti ne [3-Hydroxyoleylcarnitine] acylcarnitines Ac.Ca.
    C18:2 Octadecadienoylcarnitine [Linoleylcarnitine] acylcarnitines Ac.Ca. 36816-10-1
    C2 Acetylcarnitine acylcarnitines Ac.Ca. 4398-79-2;870-77-9;14992-62-2
    C3 Propionylcarnitine acylcarnitines Ac.Ca. 113817-31-5;17298-37-2
    C3-DC (C4-OH) 3-Hydroxybutyrylcarnitine / Malonylcarnitine acylcarnitines Ac.Ca.
    C5-OH (C3-DC-M) 3-Hydroxyisovalerylcarnitine / 3-Hydroxy-2-methylbutyryl acylcarnitines Ac.Ca.
    C4 Butyrylcarnitine / Isobutyrylcarnitine acylcarnitines Ac.Ca. 25518-49-4;25576-40-3
    C4:1 Butenoylcarnitine acylcarnitines Ac.Ca.
    C5 Isovalerylcarnitine / 2-Methylbutyrylcarnitine / Valerylcarnitine acylcarnitines Ac.Ca. 31023-24-2;31023-25-3
    C5:1 Tiglylcarnitine / 3-Methyl-crotonylcarnitine acylcarnitines Ac.Ca. 64191-86-2
    C5:1-DC Glutaconylcarnitine / Mesaconylcarnitine (Undecanoylcarnitine) acylcarnitines Ac.Ca.
    C5-DC (C6-OH) Glutarylcarnitine acylcarnitines Ac.Ca.
    C6:1 Hexenoylcarnitine acylcarnitines Ac.Ca.
    C6 (C4:1-DC) Hexanoylcarnitine [Caproylcarnitine] acylcarnitines Ac.Ca. 6920-35-0;14919-34-7
    C8:1 Octenoylcarnitine acylcarnitines Ac.Ca.
    C9 Nonanoylcarnitine [Pelargonylcarnitine] acylcarnitines Ac.Ca.
    H1 Hexoses sugars En.Met 57-48-7;59-23-4;4205-23-6;2152-76-3;87-81-0;7635-11-2;15572-79-9;5934-56-5;87-79-6;23567-25-1;10030-80-5;10030-80-5;6027-89-0;921-60-8;7776-48-9;1949-88-8;19163-87-2;3615-56-3;551-68-8;1990-29-0;50-99-7;530-26-7;492-61-5;87-79-6;492-62-6;59-23-4;3615-56-3;87-81-0;7296-15-3;7296-64-2;3646-73-9 59-23-4;23140-52-5;2595-97-3;2595-97-3;7776-48-9;15572-79-9;53188-23-1;1990-29-0;4205-23-6;5978-95-0;2595-98-4;2595-98-4;551-68-8;57-48-7;6027-89-0
    SM C16:0 sphingomyelin with acyl residue sum C16:0 sphingolipids S.L.
    SM C16:1 sphingomyelin with acyl residue sum C16:1 sphingolipids S.L.
    SM C18:0 sphingomyelin with acyl residue sum C18:0 sphingolipids S.L. 58909-84-5
    SM C18:1 sphingomyelin with acyl residue sum C18:1 sphingolipids S.L. 108392-10-5
    SM C20:2 sphingomyelin with acyl residue sum C20:2 sphingolipids S.L.
    SM C24:0 sphingomyelin with acyl residue sum C24:0 sphingolipids S.L.
    SM C24:1 sphingomyelin with acyl residue sum C24:1 sphingolipids S.L.
    SM C26:0 sphingomyelin with acyl residue sum C26:0 sphingolipids S.L.
    SM C26:1 sphingomyelin with acyl residue sum C26:1 sphingolipids S.L.
    SM (OH) C14:1 Hydroxysphingomyelin with acyl residue sum C14:1 sphingolipids S.L.
    SM (OH) C16:1 Hydroxysphingomyelin with acyl residue sum C16:1 sphingolipids S.L.
    SM (OH) C22:1 Hydroxysphingomyelin with acyl residue sum C22:1 sphingolipids S.L.
    SM (OH) C22:2 Hydroxysphingomyelin with acyl residue sum C22:2 sphingolipids S.L.
    SM (OH) C24:1 Hydroxysphingomyelin with acyl residue sum C24:1 sphingolipids S.L.
    Ala Alanine aminoacids Am.Ac. 56-41-7;107-95-9;338-69-2;302-72-7
    Arg Arginine aminoacids Am.Ac. 74-79-3;157-06-2;7200-25-1
    Asn Asparagine aminoacids Am.Ac. 70-47-3;2058-58-4;3130-87-8
    Asp Aspartic acid aminoacids Am.Ac. 56-84-8;1783-96-6;617-45-8
    Cit Citrulline aminoacids Am.Ac. 627-77-0;372-75-8
    Gln Glutamine aminoacids Am.Ac. 56-85-9;6899-04-3;5959-95-5
    Glu Glutamate aminoacids Am.Ac. 56-86-0;6893-26-1;617-65-2
    Gly Glycine aminoacids Am.Ac. 56-40-6
    His Histidine aminoacids Am.Ac. 71-00-1;4998-57-6;351-50-8
    Ile Isoleucine aminoacids Am.Ac. 73-32-5;1509-34-8;319-78-8;1509-35-9;443-79-8
    Leu Leucine aminoacids Am.Ac. 40469-85-0;5699-54-7;61-90-5;328-38-1;75992-50-6;328-39-2
    Lys Lysine aminoacids Am.Ac. 56-87-1;923-27-3;70-54-2
    Met Methionine aminoacids Am.Ac. 63-68-3;348-67-4;59-51-8
    Orn Ornithine aminoacids Am.Ac. 70-26-8;348-66-3;616-07-9
    Phe Phenylalanine aminoacids Am.Ac. 63-91-2;150-30-1 ;673-06-3
    Pro Proline aminoacids Am.Ac. 147-85-3;344-25-2;609-36-9
    Ser Serine aminoacids Am.Ac. 56-45-1;302-84-1;312-84-5
    Thr Threonine aminoacids Am.Ac. 80-68-2;72-19-5;632-20-2;28954-12-3;24830-94-2
    Trp Tryptophane aminoacids Am.Ac. 73-22-3;153-94-6;54-12-6
    Tyr Tyrosine aminoacids Am.Ac. 60-18-4;556-03-6;556-02-5
    Val Valine aminoacids Am.Ac. 72-18-4;640-68-6;516-06-3
    Ac-Orn N-acetylornithine biogenic amines B.Am. 6205-Aug-09
    ADMA Asymmetric dimethylarginine biogenic amines B.Am. 102783-24?-4;30315-93-6
    alpha-AAA 2-Aminoadipic acid biogenic amines B.Am. 7620-28-2;542-32-5;1118-90-7
    Carnosine Carnosine biogenic amines B.Am. 7683-28-5;305-84-0
    Creatinine Creatinine biogenic amines B.Am. 60-27-5
    Histamine Histamine biogenic amines B.Am. 51-45-6
    Kynurenine Kynurenine biogenic amines B.Am. 13441-51-5;2922-83-0;343-65-7
    Met-SO Methionine-Sulfoxide biogenic amines B.Am. 62697-73-8;3226-65-1
    Sarcosine Sarcosine biogenic amines B.Am. 107-97-1
    SDMA Symmetric dimethylarginine biogenic amines B.Am.
    Serotonin Serotonin biogenic amines B.Am. 50-67-9
    Spermidine Spermidine biogenic amines B.Am. 124-20-9
    Taurine Taurine biogenic amines B.Am. 107-35-7
    total DMA Total dimethylarginine biogenic amines B.Am. 102783-24?-4;30315-93-6
    20a-OH-C 20α -Hydroxycholesterol oxysterols O.St. 516-72-3
    22R-OH-C 22-R-Hydroxycholesterol oxysterols O.St. 22348-64-7
    24,25-EpoxyC 24,25-Epoxycholesterol oxysterols O.St. 77058-74-3
    24-DH-Lanosterol 24-Dihydrolanosterol oxysterols O.St. 79-62-9
    24S-OH-C 24-S-Hydroxycholesterol oxysterols O.St. 474-73-7
    25-OH-C 25-Hydroxycholesterol oxysterols O.St. 2140-46-7
    27-OH-C 27-Hydroxycholesterol oxysterols O.St. 20380-11-4;26259-77-8
    5a,6a-EpoxyC 5α ,6α -Epoxycholesterol oxysterols O.St. 1250-95-9
    Cholestenone Cholestenone oxysterols O.St. 601-57-0
    Desmosterol Desmosterol oxysterols O.St. 313-04-2
    3b,5a,6b-THC 3β,5α ,6β-Trihydroxychotestan oxysterols O.St. 1253-84-5
    8-iso-PGF2a 8-iso-Prostaglandin F2alpha prostaglandins P.G. 27415-26-5
    AA Arachidonic acid prostaglandins P.G. 506-32-1
    DHA Docosahexaenoic acid prostaglandins P.G. 6217-54-5;25167-62-8;25377-50-8
    LTB4 Leukotriene B4 prostaglandins P.G. 71160-24-2;73151-67-4;71160-24-2
    TXB2 Tromboxane B2 prostaglandins P.G. 54397-85-2
    En.Met. = Energy metabolite; Ac.Ca. = Acyl carnitine; S.L. = sphingolipid; Am.Ac. = amiono acid; B.Am. = biogenic amine; O.St. = oxysterol; P.G. = prostaglandin
  • As used here, the term " metabolite" or " metabolic marker" or " low molecular weight metabolic marker" denotes endogenous organic compounds of a cell, an organism, a tissue or being present in body liquids, in particular blood, and in extracts or fractions obtained from the aforementioned sources. Typical examples of metabolites are carbohydrates, lipids, phospholipids, sphingolipids and sphingophospholipids, amino acids, cholesterol, steroid hormones and oxidized sterols and other compounds such as collected in the Human Metabolite database [Wishart DS et al., HMDB: the Human Metabolome Database. Nucleic Acids Res. 2007 Jan; 35 (Database issue):D521-6 (see http://www.hmdb.ca/ )] and other databases and literature. This includes any substance produced by metabolism or by a metabolic process and any substance involved in metabolism. In particular, suitable metabolites are defined in above Table 1. More particular, they may have a molecular weight typically of up to1500 Dalton, as for example in the range of 50 to 1500 Dalton.
  • More particularly the present invention also refers to " Hippocampus-specific" metabolites. They are listed in subsequent Table 2. These metabolites, individually or combinations of several of such metabolites, may be applied as markers for brain injury affecting the hippocampus of an infant. Table 2: " Hippocampus-specific" metabolites
    No Short name Full name Contribution
    1 Lac Lactate +
    2 Fum Fumaric acid +
    3 Ac-Orn N-acetylornithine +
    4 Carnosine Carnosine -
    5 C5:1-DC Glutaconylcarnitine / Mesaconylcarnitine (Undecanoylcarnitine) +
    6 C16:2 Hexadecadienoylcarnitine +
    7 Pent-P Pentosephosphate (e.g. Ribose-5-phosphate + Ribulose-5-phosphate) +
    8 C10:2 Decadienoylcarnitine -
    9 Met-SO Methionine-Sulfoxide +
    10 SM (OH) C22:2 Hydroxysphingomyelin with acyl residue sum C22:2 -
    11 SM C24:1 sphingomyelin with acyl residue sum C24:1 -
    12 ADMA Asymmetric dimethylarginine +
    13 C5:1 Tiglylcarnitine / 3-Methyl-crotonylcarnitine -
    14 3b,5a,6b-THC 3β,5α,6β-Trihydroxycholestan +
    15 27-OH-C 27-Hydroxycholesterol +
    16 Suc Succinic acid +
    17 8-iso-PGF2a 8-iso-Prostaglandin F2alpha +
    18 total DMA Total dimethylarginine +
    19 25-OH-C 25-Hydroxycholesterol +
    20 SM (OH) C22:1 Hydroxysphingomyelin with acyl residue sum C22:1 -
    21 Creatinine Creatinine -
    22 Phe Phenylalanine +
    23 C4:1 Butenoylcarnitine -
    24 LTB4 Leukotriene B4 +
    25 24S-OH-C 24-S-Hydroxycholesterol +
    26 Orn Ornithine +
    27 Cit Citrulline -
    28 SM (OH) C14:1 Hydroxysphingomyelin with acyl residue sum C14:1 -
    29 H1 Hexoses -
    30 C8:1 Octenoylcarnitine -
    31 5a,6a-EpoxyC 5α,6α-Epoxycholesterol +
    32 alpha-AAA 2-Aminoadipic acid +
    33 Pro Proline +
    34 Lys Lysine +
    35 Arg Arginine +
    36 SM C16:1 sphingomyelin with acyl residue sum C16:1 -
    37 SDMA Symmetric dimethylarginine +
    38 Met Methionine +
    39 Gln Glutamine +
    40 SM C26:1 sphingomyelin with acyl residue sum C26:1 -
    41 SM C18:1 sphingomyelin with acyl residue sum C18:1 -
    42 Hex-P Hexosephosphate (e.g. Glucose-1-phosphate + Glucose-6-phosphate + Fructose-6-phosphate) -
    Contribution:
    + = increased level/ concentration versus control in case of damage of hippocampus
    - = decreased level/ concentration versus control in case of damage of hippocampus
  • The present invention also refers to " Basal ganglia-specific" metabolites. They are listed in subsequent Table 3. These metabolites, individually or combinations of several of such metabolites, may be applied as markers for brain injury affecting basal ganglia of an infant. Table 3: " Basal ganglia-specific" metabolites
    No Short name Full name Contribution
    1 Met Methionine +
    2 SM (OH) C22:2 Hydroxysphingomyelin with acyl residue sum C22:2 -
    3 SM (OH) C14:1 Hydroxysphingomyelin with acyl residue sum C14:1 -
    4 Met-SO Methionine-Sulfoxide +
    5 SM C16:1 sphingomyelin with acyl residue sum C16:1 -
    6 SM (OH) C22:1 Hydroxysphingomyelin with acyl residue sum C22:1 -
    7 Pro Proline +
    8 Tyr Tyrosine +
    9 Gln Glutamine +
    10 SM C24:1 sphingomyelin with acyl residue sum C24:1 -
    11 SM C24:0 sphingomyelin with acyl residue sum C24:0 -
    12 SM C16:0 sphingomyelin with acyl residue sum C16:0 -
    13 Orn Ornithine +
    14 Ac-Orn N-acetylornithine +
    15 Arg Arginine +
    16 SM C18:1 sphingomyelin with acyl residue sum C18:1 -
    17 alpha-KGA alpha-Ketoglutaric acid -
    18 Trp Tryptophane +
    19 SM (OH) C24:1 Hydroxysphingomyelin with acyl residue sum C24:1 -
    20 SM (OH) C16:1 Hydroxysphingomyelin with acyl residue sum C16:1 -
    21 Cholestenone Cholestenone -
    22 C5:1-DC Glutaconylcarnitine / Mesaconylcarnitine (Undecanoylcarnitine) +
    23 Lys Lysine +
    24 Histamine Histamine -
    25 His Histidine +
    26 Lac Lactate +
    27 Phe Phenylalanine +
    28 C6:1 Hexenoylcarnitine +
    29 SM C18:0 sphingomyelin with acyl residue sum C18:0 -
    30 120a-OH-C 20α-Hydroxycholesterol +
    31 24-DH-Lanosterol 24-Dihydrolanosterol -
    32 Kynurenine Kynurenine +
    33 Leu Leucine +
    34 SM C20:2 sphingomyelin with acyl residue sum C20:2 -
    35 Ala Alanine +
    36 C14:1 Tetradecenoylcarnitine [Myristoleylcarnitine] -
    37 LTB4 Leukotriene B4 +
    38 Suc Succinic acid +
    39 TXB2 Tromboxane B2 +
    40 Fum Fumaric acid +
    41 Gly Glycine +
    42 25-OH-C 25-Hydroxycholesterol -
    43 SM C26:1 sphingomyelin with acyl residue sum C26:1 -
    44 Ser Serine +
    45 alpha-AAA 2-Aminoadipic acid +
    46 8-iso-PGF2a 8-iso-Prostaglandin F2alpha +
    47 Val Valine +
    48 Asn Asparagine +
    49 Pent-P Pentosephosphate (e.g. Ribose-5-phosphate + Ribulose-5-phosphate) +
    50 total DMA Total dimethylarginine +
    51 Creatinine Creatinine -
    Contribution:
    + = increased level/ concentration versus control in case of damage of basal ganglia
    - = decreased level/ concentration versus control in case of damage of basal ganglia
  • The present invention also refers to " Neurological behavioural score-specific" metabolites. They are listed in subsequent Table 4. These metabolites, individually or combinations of several of such metabolites, may be applied as markers for neurological behavioural deficits of an infant. Table 4: " Neurological behavioural score-specific" metabolites
    No. Short name Full name Contribution
    1 27-OH-C 27-Hydroxycholesterol +
    2 Fum Fumaric acid +
    3 Carnosine Carnosine -
    4 total DMA Total dimethylarginine +
    5 C5-DC (C6-OH) Glutarylcarnitine +
    6 SDMA Symmetric dimethylarginine +
    7 C5:1 Tiglylcarnitine / 3-Methyl-crotonylcarnitine -
    8 Met-SO Methionine-Sulfoxide +
    9 C10:2 Decadienoylcarnitine -
    10 SM (OH) C22:2 Hydroxysphingomyelin with acyl residue sum C22:2 -
    11 C8:1 Octenoylcarnitine -
    12 Phe Phenylalanine +
    13 Ac-Orn N-acetylornithine +
    14 SM (OH) C14:1 Hydroxysphingomyelin with acyl residue sum C14:1 -
    15 24,25-EpoxyC 24,25-Epoxycholesterol +
    16 Tyr Tyrosine +
    17 alpha-AAA 2-Aminoadipic acid +
    18 C14:1 Tetradecenoylcarnitine [Myristoleylcarnitine] -
    19 Pent-P Pentosephosphate (e.g. Ribose-5-phosphate + Ribulose-5-phosphate) +
    20 C6 (C4:1-DC) Hexanoylcarnitine [Caproylcarnitine] -
    21 SM C16:1 sphingomyelin with acyl residue sum C16:1 -
    22 C14:1-OH 3-Hydroxytetradecenoylcarnitine [3-Hydroxymyristoleylcarnitine] -
    23 SM C24:1 sphingomyelin with acyl residue sum C24:1 -
    24 Cholestenone Cholestenone -
    25 Lac Lactate +
    26 8-iso-PGF2a 8-iso-Prostaglandin F2alpha +
    27 3b,5a,6b-THC 3β,5α,6β-Trihydroxycholestan -
    28 Suc Succinic acid +
    29 C0 Carnitine (free) +
    30 24-DH-Lanosterol 24-Dihydrolanosterol -
    31 Val Valine +
    32 SM C16:0 sphingomyelin with acyl residue sum C16:0 -
    33 C3-DC (C4-OH) 3-Hydroxybutyrylcarnitine / Malonylcarnitine +
    34 Lys Lysine +
    35 Leu Leucine +
    36 SM C26:0 sphingomyelin with acyl residue sum C26:0 +
    37 Cit Citrulline +
    38 LTB4 Leukotriene B4 +
    39 5a,6a-EpoxyC 5α,6α-Epoxycholesterol -
    40 C4:1 Butenoylcarnitine -
    41 Met Methionine +
    42 C5:1-DC Glutaconylcarnitine / Mesaconylcarnitine (Undecanoylcarnitine) +
    43 Pro Proline +
    44 SM (OH) C16:1 Hydroxysphingomyelin with acyl residue sum C16:1 -
    45 C14:2-OH 3-Hydroxytetradecadienoylcarnitine +
    46 Thr Threonine +
    47 SM (OH) C22:1 Hydroxysphingomyelin with acyl residue sum C22:1 -
    Contribution:
    + = increased level/ concentration versus control in case of neurological behavioural deficits
    - = decreased level/ concentration versus control in case of neurological behavioural deficits
  • " Metabolomics" as understood within the scope of the present invention designates the comprehensive qualitative, or in particular quantitative measurement of several metabolites as defined herein; in particular by, but not limited to, analytical methods such as mass spectrometry, coupling of liquid chromatography, gas chromatography and other separation methods, like chromatography with mass spectrometry.
  • The term " metabolism" refers to the chemical changes that occur within the tissues of an organism, including " anabolism" and " catabolism" . Anabolism refers to biosynthesis or the buildup of molecules and catabolism refers to the breakdown of molecules.
  • A " biomarker" in this context is a characteristic, comprising concentration data of at least two, as for example 2, 3, 4, 5, 6, 7, 8, 9 or 10, metabolites (also designated as a " panel" of metabolites, " signature" of metabolites, " model" or" profile" using quantitative data or concentration data directly or processed by any mathematical transformation (e.g. by a classification method) and evaluated as an indicator of biologic processes, pathogenic processes, or responses to a therapeutic intervention associated with NE in infants.
  • A " score" in the context of the invention denotes a value, in particular a quantitative value, generated from metabolite data by means of any mathematical transformation or by subjecting to any mathematical equation and comparing these data to data or mathematically transformed or processed data of a reference population.
  • The " onset of NE in infants" refers to an early stage of NE in infants, i.e., prior to a stage when the clinical manifestations are sufficient to support a clinical suspicion of brain injury in infants. The exact mechanism by which a patient acquires NE in infants is not a critical aspect of the invention. The methods of the present invention can detect changes in the biomarker score independent of the origin of the brain injury in infants. Regardless of how NE in infants arises (as for example by asphyxia, hypoxia and/or ischemia), the methods of the present invention allow for determining the status of a patient having, or suspected of having, NE, as classified by previously used criteria.
  • " Specific" in the context of " specific metabolites" as used above may not necessarily be understood as if said metabolite is exclusively detected in or associated with a certain disease or damage. However, changes in level or concentration of said metabolite when a certain disease or damage emerges may be more significant than in another type of disease or damage.
  • As used herein, the term " NE in infants-specific metabolite" refers to metabolites that are differentially present or differentially concentrated in an infant suffering from NE compared to healthy infant.
  • A " specific metabolite" or " NE in infants- specific metabolite" is preferably differentially present at a level that is statistically significant (e.g., an adjusted p-value less than 0.05 as determined using either linear model including Analysis of Variance and Welch' s t-test or its non parametric equivalent versions). Exemplary NE in infants - specific metabolites are described herein.
  • " NE in infants- specific" metabolites encompass the groups of " hippocampus-specific" (or " hippocampus damage-specific" ), " basal-ganglia-specific" (or " basal ganglia damage-specific" ) or " Neurological behavioural score-specific" metabolites (see Tables 2, 3 and 4).
  • The term " differentially present" or " differentially concentrated" describes the situation that a metabolite is present in increased or decreased level or concentration in a sample obtained from an NE patient if compared to level or concentration of said metabolite observed for one or more otherwise healthy individuals, i.e. not suffering from NE.
  • A " biological sample" may contain any biological material suitable for detecting the desired biomarkers, and may comprise cellular and/or non-cellular material from a subject. The sample can be isolated from any suitable biological tissue or body fluid such as, for example, tissue, and, in particular, blood, blood plasma, and blood serum. The sample may be analyzed without or after a pre-treatment. Examples of pre-treated samples are pre-treated blood, like EDTA-blood, or EDTA-plasma, citrate-plasma, heparin plasma. The originally obtained samples or fractions thereof may be further modified by methods known in the art, as for example by fractionation or dilution. Fractionation may be performed to remove constituents which might disturb the analysis. Dilution may be performed by mixing, the original sample or fraction with a suitable sample liquid, like a suitable buffer, in order to adjust the concentration the constituents, as for example of the analyte. Such modified samples exemplify samples " derived from" the original body fluid sample collected or isolated from the body of the individual.
  • A " reference level" of a metabolite means a level of the metabolite that is indicative of a particular disease state, phenotype, or lack thereof, as well as combinations of disease states, phenotypes, or lack thereof. A " positive" reference level of a metabolite means a level that is indicative of a particular disease state or phenotype. A " negative" reference level of a metabolite means a level that is indicative of a lack of a particular disease state or phenotype. For example, a " NE in infants- positive reference level" of a metabolite means a level of a metabolite that is indicative of a positive diagnosis of NE in infants in a subject, and a " NE in infants- negative reference level" of a metabolite means a level of a metabolite that is indicative of a negative diagnosis of NE in infants in a subject. A " reference level" of a metabolite may be an absolute or relative amount or concentration of the metabolite, a presence or absence of the metabolite, a range of amount or concentration of the metabolite, a minimum and/or maximum amount or concentration of the metabolite, a mean amount or concentration of the metabolite, and/or a median amount or concentration of the metabolite; and, in addition, " reference levels" of combinations of metabolites may also be ratios of absolute or relative amounts or concentrations of two or more metabolites with respect to each other or a composed value / score obtained by a statistical model.
  • As used herein, the term " processor" refers to a device that performs a set of steps according to a program (e.g., a digital computer). Processors, for example, include Central Processing Units (" CPUs" ), electronic devices, or systems for receiving, transmitting, storing and/or manipulating data under programmed control.
  • As used herein, the term " memory device," or " computer memory" refers to any data storage device that is readable by a computer, including, but not limited to, random access memory, hard disks, magnetic (floppy) disks, compact discs, DVDs, magnetic tape, flash memory, and the like.
  • " Mass Spectrometry" (MS) is a technique for measuring and analysing molecules that involves fragmenting a target molecule, then analysing the fragments, based on their mass/charge ratios, to produce a mass spectrum that serves as a " molecular fingerprint" . Determining the mass/charge ratio of an object is done through means of determining the wavelengths at which electromagnetic energy is absorbed by that object. There are several commonly used methods to determine the mass to charge ratio of an ion, some measuring the interaction of the ion trajectory with electromagnetic waves, others measuring the time an ion takes to travel a given distance, or a combination of both. The data from these fragment mass measurements can be searched against databases to obtain definitive identifications of target molecules.
  • The term " separation" refers to separating a complex mixture into its component proteins or metabolites. Common laboratory separation techniques include gel electrophoresis and chromatography.
  • The term " capillary electrophoresis" refers to an automated analytical technique that separates molecules in a solution by applying voltage across buffer-filled capillaries. Capillary electrophoresis is generally used for separating ions, which move at different speeds when the voltage is applied, depending upon the size and charge of the ions. The solutes (ions) are seen as peaks as they pass through a detector and the area of each peak is proportional to the concentration of ions in the solute, which allows quantitative determinations of the ions.
  • The term " chromatography" refers to a physical method of separation in which the components to be separated are distributed between two phases, one of which is stationary (stationary phase) while the other (the mobile phase) moves in a definite direction. Chromatographic output data may be used for manipulation by the present invention.
  • A " mass spectrum" is a plot of data produced by a mass spectrometer, typically containing m/z values on x-axis and intensity values on y-axis.
  • A " peak" is a point on a mass spectrum with a relatively high y-value.
  • The term " m/z" refers to the dimensionless quantity formed by dividing the mass number of an ion by its charge number. It has long been called the " mass-to-charge" ratio.
  • As used herein, the terms " detect" , " detecting" , or " detection" may describe either the general act of discovering or discerning or the specific observation of a detectable compound or composition or metabolite or biomarker.
  • " Assessing" or " assessment" is intended to include both quantitative and qualitative determination in the sense of obtaining an absolute value for the amount or concentration of the metabolite or metabolites to be analyzed present in the sample, and also obtaining an index, ratio, percentage or other value indicative of the level of metabolite in the sample. Assessment may be direct or indirect and the chemical species actually detected need not of course be the analyte itself but may for example be a derivative thereof. The purpose of such assessment of metabolite(s) may be different. In particular, an assessment may be performed for evaluating the likelihood (or risk) of brain damage or encephalopathy to occur in a patient. Purpose of an assessment may also be the determination of the severity (severity assessment) of brain damage or encephalopathy (optionally already diagnosed) and long-term neurological outcome in a patient. Assessment also encompasses the analysis of progression or regression of brain damage or encephalopathy. Assessment in the context of the invention also encompasses identification and/or differentiation of brain areas (as, for example, hippocampus and basal ganglia) affected (optionally to a different extent) by said damage.
  • Unless otherwise stated, the expression " patient" refers in particular to a " neonatal" patient, in particular pre-term born, or term born baby.
  • As used herein, the term "clinical failure" refers to a negative outcome following NE treatment in infants.
  • " Accuracy" or "predictive ability" as used herein is, unless otherwise stated, as defined in the experimental section, below.
  • b) Particular embodiments of the invention
  • The present invention refers to the following particular embodiments:
    1. 1. An in vitro or in vivo diagnostic method for early assessing encephalopathy, in particular NE in a mammalian patient, which method comprises
      1. a) optionally obtaining a blood sample, as for example whole blood, serum or plasma sample, of said patient and
      2. b) assessing in said blood sample at least one, like 1 to 100, 1 to 50, 1 to 25, 1 to 10 or 2, 3, 4, 5 or 6 panels (models) of low molecular weight endogenous early metabolic markers indicative of and/ or specific for the presence or absence, in particular presence, of encephalopathy, in particular NE, in said patient.
      Said assessment may also comprise the differentiation between affected (damaged) and non- affected (non-damaged) brain areas and/or may comprise predicting the neurological behavioural outcome of the patient.
      In vitro methods usually do not encompass step a) while in vivo methods of the invention may comprise said step a) and/or another method step performed to the patient.
    2. 2. The method of embodiment 1, wherein said mammalian patient is a human neonate.
    3. 3. The method of embodiment 1, wherein said human neonate is suspected to suffer from a NE.
    4. 4. The method of one of the embodiments 2 and 3, wherein said blood sample is obtained immediately, at an early as possible stage, in particular 1 minute to 6hours, like 2 to 180 or 5 to 120 minutes after birth or after initiating resuscitation or suspicion of NE.
    5. 5. The method of one of the preceding embodiments, wherein said brain injury predominantly affects one or more specific brain areas, in particular basal ganglia and/or the hippocampus of the neonatal brain and/or causes behavioural deficits of the child.
    6. 6. The method of one of the preceding embodiments, wherein said panel of low molecular early metabolic markers indicative of the presence of NE comprises at least 2, like 2, 3, 4, 5, 6, or 7, different metabolites selected from at least one of the following classes of chemical substances:
      1. a) low molecular organic carboxylic acids, like saturated or non-saturated mono- or polyvalent C1-C20- or C2-C10-carboxylic acids, in particular mono- or dicarboxylic acids, optionally substituted by one or more hydroxy or keto-groups; their salts, ester or anhydrides;
      2. b) sugars, like pentoses and hexoses, and phosphate derivatives thereof,
      3. c) acylcarnitines,
      4. d) sphingomyelins,
      5. e) amino acids,
      6. f) biogenic amines
      7. g) oxysterols, and
      8. h) prostaglandins
    7. 7. The method of one of the preceding embodiments, wherein said panel (model) of low molecular early metabolic markers indicative of the presence of NE comprises at least 2, like 2, 3, 4, 5, 6, or 7, metabolites selected from at least one of the following functional classes of metabolites
      1. a) energy metabolism related metabolites indicating the occurrence of or the previous lack of oxygen
      2. b) metabolite markers of oxidative stress and anti-oxidative capacities
      3. c) metabolite with neurotoxic or neuroprotective potential,
      4. d) metabolite markers predominantly occurring in the brain.
    8. 8. The method of one of the preceding embodiments, wherein said panel (model) is indicative of the presence of NE with high statistic significance, as for example with an accuracy of at least 75, in particular at least about 80, as for example at least about 85, 90, 91, 92, 93, 94, 95, 96, 97, 98 or 99, , as, for example, determined in a non-human animal model (for example piglet animal model).
    9. 9. The method of one of the preceding embodiments, wherein said chemical classes of metabolites comprise the following individual members:
      1. a) low molecular weight organic carboxylic acids, selected from dicarboxylic acids, like alpha-ketoglutaric acid, fumaric acid and succinic acid, and monocarboxylic acids, like lactic acid, pyruvic acid and oxaloacetic acid; in particular lactic acid
      2. b) sugars, selected from like hexoses and hexosephosphates, like glucose-1-phosphate, glucose-6-phosphate, fructose-6-phosphate and pentose phospates, like ribose-5-phosphate and ribulose-5-phosphate;
      3. c) acylcarnitines, like carnitine (free), decanoylcarnitine, decadienoylcarnitine, dodecanoylcarnitine, tetradecenoylcarnitine, 3-hydroxytetradecenoylcarnitine, tetradecadienoylcarnitine, 3-hydroxytetradecadienoylcarnitine, hexadecanoylcarnitine, hexadecadienoylcarnitine, octadecanoylcarnitine, octadecenoylcarnitin, 3-hydroxyoctadecenoylcarnitine, octadecadienoylcarnitine, acetylcarnitine, propionylcarnitine, 3-hydroxybutyrylcarnitine, malonylcarnitine, 3-hydroxyisovalerylcarnitine (3-hydroxy-2-methylbutyrylcarnitine), butyrylcarnitine, isobutyrylcarnitine, butenoylcarnitine, isovalerylcarnitine, 2-methylbutyrylcarnitine, valerylcarnitine, tiglylcarnitine, 3-methyl-crotonylcarnitine, glutaconylcarnitine, mesaconylcarnitine (undecanoylcarnitine), glutarylcarnitine, hexenoylcarnitine, hexanoylcarnitine, octenoylcarnitine and nonanoylcarnitine,; in particular, carnitine (free), decadienoylcarnitine, tetradecenoylcarnitine, 3-hydroxytetradecenoylcarnitine, tetradecadienoylcarnitine, 3-hydroxytetradecadienoylcarnitine, hexadecadienoylcarnitine, 3-hydroxybutyrylcarnitine, 3-hydroxyisovalerylcarnitine (3-hydroxy-2-methylbutyrylcarnitine), butenoylcarnitine, tiglylcarnitine, glutaconylcarnitine, mesaconylcarnitine (undecanoylcarnitine), glutarylcarnitine, hexenoylcarnitine, hexanoylcarnitine, octenoylcarnitine
      4. d) sphingomyelins, like sphingomyelin with acyl residue sum C16:0, sphingomyelin with acyl residue sum C16:1, sphingomyelin with acyl residue sum C18:0, sphingomyelin with acyl residue sum C18:1, sphingomyelin with acyl residue sum C20:2, sphingomyelin with acyl residue sum C24:0, sphingomyelin with acyl residue sum C24:1, sphingomyelin with acyl residue sum C26:0 and sphingomyelin with acyl residue sum C26:1, hydroxysphingomyelin with acyl residue sum C14:1, hydroxysphingomyelin with acyl residue sum C16:1, hydroxysphingomyelin with acyl residue sum C22:1, hydroxysphingomyelin with acyl residue sum C22:2, hydroxysphingomyelin with acyl residue sum C24:1;
      5. e) amino acids, like alanine, arginine, asparagine, aspartic acid, citrulline, glutamine, glutamate, glycine, histidine, isoleucine, leucine, lysine, methionine, ornithine, phenylalanine, proline, serine, threonine, tryptophane, tyrosine and valine; in particular, alanine, arginine, asparagine, citrulline, glutamine, glycine, histidine, leucine, lysine, methionine, ornithine, phenylalanine, proline, serine, threonine, tryptophane, tyrosine and valine;
      6. f) biogenic amines, like N-acetylornithine, asymmetric dimethylarginine, 2-aminoadipic acid, carnosine, creatinine, histamine, kynurenine, methionine-sulfoxide, sarcosine, symmetric dimethylarginine, serotonin,spermidine, taurine and total dimethylarginine; in particular, N-acetylornithine, asymmetric dimethylarginine, 2-aminoadipic acid, carnosine, creatinine, histamine, kynurenine, methionine-sulfoxide, symmetric dimethylarginine and total dimethylarginine;
      7. g) oxysterols, like 20α -hydroxycholesterol, 22-R-hydroxycholesterol, 24,25-epoxycholesterol, 24-dihydrolanosterol, 24-S-hydroxycholesterol, 25-hydroxycholesterol, 27-hydroxycholesterol, 5α ,6α -epoxycholesterol, cholestenone, desmosterol and 3β,5α 6β-trihydroxycholestan; in particular, 20α -hydroxycholesterol, 24,25-epoxycholesterol, 24-dihydrolanosterol, 24-S-hydroxycholesterol, 25-hydroxycholesterol, 27-hydroxycholesterol, 5α ,6α -epoxycholesterol, cholestenone and 3β,5α ,6β-trihydroxycholestan;
      8. h) prostaglandins, like 8-iso-prostaglandin F2alpha, arachidonic acid, docosahexaenoic acid, leukotriene B4 and tromboxane B2; in particular, like 8-iso-prostaglandin F2alpha, leukotriene B4 and tromboxane B2..
    10. 10. The method of one of the preceding claims, wherein said functional classes of metabolites comprise the following individual members:
      1. a) energy metabolism related metabolites indicating the occurrence or previous lack of oxygen, like alanine, fumarate, succinate, alpha-ketoglutaric acid , decadienoyl carnitines and mesaconylcarnitine;
      2. b) metabolites of oxidative stress and anti-oxidative capacities and inflammation, like methioninsulfoxide, hydroxykynurenine and and hydroxysphingomyelins and sphingomyelins; in particular, methioninsulfoxide, hydroxysphingomyelins and sphingomyelins;
      3. c) metabolites with neurotoxic or neuroprotective potential, like 2-aminoadipic acid, carnosine" hydroxykynurenine,kynurenine,spermidine, Serotonin, and spermin, in particular, 2-aminoadipic acid, carnosine, kynurenine;and
      4. d) metabolites predominantly occurring in the brain, like 25-hydroxycholesterol, 24-hydroxycholesterol, 24,25-epoxycholesterol.
    11. 11. The method of one of the preceding embodiments, wherein said at least one, like 1 to 100, 1 to 50, 1 to 25, 1 to 10 or 2, 3, 4, 5 or 6 panels indicative of the presence of brain injury, are selected within one of the following sets of models:
      1. a) set of hippocampus damage-related models 1 to 145 of Table 8;
      2. b) set of basal ganglia damage-related models 1 to 3945 of Table 9; or
      3. c) set of neurological behavioural abnormality-related models 1 to 717 of Table 10.
    12. 12. The method of one of the preceding embodiments, wherein said panel of metabolic markers comprises at least one first metabolic marker (lead marker or lead metabolite), like 1, 2, 3, 4, 5, 6, or 7 markers selected form:
      • a) fumarate (Fum);
      • b) carnosine (Car);
      • c) 24,25-epoxycholesterol (24,25 EpoxyC);
      • d) alpha-aminoadipic acid (alpha-AAA);
      • e) hydroxysphingomyelin with acyl residue sum C22:2 (SM(OH) C22:2);
      • f) methionine sulfoxide (Met-SO);
      • g) hydroxysphingomyelin with acyl residue sum C14:1 (SM(OH) C14:1);
      • h) alpha-ketoglutaric acid (alpha-KGA);
      • i) cholestenone;
      • k) sphingomyelin with acyl residue sum C16:1 (SM C16:1)
      • l) decadienoyl carnitine (C10:2);
      • m) sphingomyelin with acyl residue sum C24:1 (SM C24:1);
      • n) mesaconylcarnitine (C5:1-DC); and
      • o) succinate (Suc).
      optionally in combination with at least one, like 1, 2, 3, 4, 5, or 6, second marker different from said lead markers and selected from the markers as defined in anyone of said claims 6 to 9 or above tables 1 to 4.
    13. 13. The method of embodiment 12, wherein
      1. a) hippocampus damage-related panels comprise as lead marker C10:2; SM C24:1; C5:1-DC and/or Suc;
      2. b) basal ganglia damage-related panels comprise as lead marker Met-SO; SM(OH) C14:1; alpha-KGA, Cholestenone and/or SM C16:1; and
      3. c) neurological behavioural abnormality-related panels comprise as lead marker Fum; Car; 24,25-EpoxyC; alpha-AAA; and/or SM(OH) C22:2.
    14. 14. The method of embodiment 13, wherein said panels are selected from one of the following sets of panels:
      1. a) set of hippocampus damage-related panels 1 to 25 of Table 11;
      2. b) set of basal ganglia damage-related panels 1 to 181 of Table 12 ; or
      3. c) set of neurological behavioural abnormality-related panels 1 to 163 of Table 13.
    15. 15. The method of one of the preceding embodiments, wherein the metabolites are detected by nuclear magnetic resonance spectroscopy (NMR), mass spectroscopy, ELISA, fluorescence labeling techniques, flow cytometry, chromatography, capillary electrophoresis or chemical sensor.
    16. 16. An in vitro or in vivo diagnostic method for early differentiating types of brain damage, selected from damages of the brain compartments hippocampus and basal ganglia, in human neonates,
      which method comprises
      1. a) optionally obtaining a blood sample of said neonate and
      2. b) assessing in said body fluid sample at least one panel (model) of low molecular early metabolic markers indicative of the presence of brain injury in a brain compartment, selected from hippocampus and basal ganglia; in particular et least one panel (model) selected from panels of hippocampus damage-related panels 1 to 145 of Table 8 or 1 to 25 of Table 11; and basal ganglia damage-related panels 1 to 3945 of Table 9 or 1 to 181 of Table 12.
    17. 17. An in vitro or in vivo diagnostic method for early predicting a neurological behavioural abnormality caused by neonatal encephalopathy in human neonates,
      which method comprises
      1. a) optionally obtaining a body fluid (blood, serum) sample of said neonate and
      2. b) assessing in said body fluid sample at least one panel (model) of low molecular early metabolic markers indicative of neonatal encephalopathy-related behavioural abnormality, in particular et least one panel (model) selected from panels (models) 1 to 717 of Table 10 or panels 1 to 183 of Table 13.
    18. 18. The method of one of the preceding embodiments, wherein assessing said blood sample comprises:
      1. a) detecting said panel of metabolites;
      2. b) determining a profile of said detected metabolites; and
      3. c) comparing the profile of the detected metabolites to a standard metabolite profile, thereby diagnosing said disease or damage.
    19. 19. The method of one of the preceding embodiments, wherein an increase or decrease (versus standard/control/level of metabolites in healthy mammal) of at least one of said metabolites of said at least one panel is observed.
    20. 20. A method of assessing the progression or regression of neonatal encephalopathy which method comprises performing an in vitro diagnostic method of any one of the embodiments 1 to 19, repeating said method at least once, and comparing the obtained set of analytical parameter for said panel of metabolites with the previously determined set.
    21. 21. A method of treating a mammalian patient, in particular human neonate suffering from neonatal encephalopathy, which method comprising
      1. a) performing a diagnostic method of anyone of the embodiments 1 to 19 and
      2. b) treating a mammalian patient, in particular a neonate who as been positively assessed for neonatal encephalopathy in order to reduce disease symptoms.
    22. 22. The method of embodiment 21 , wherein said treatment comprises hypothermia.
    23. 23. A panel of early metabolic metabolites as defined in anyone of the Tables 8, 9 , 10, 11, 12 or 13 for use in diagnosis.
    24. 24. A kit for assessing the disease state of a neonatal encephalopathy in a blood sample of a mammalian patient, comprising:
      1. a) means for measuring a panel of low molecular early metabolic markers indicative of (specific for) the presence of neonatal encephalopathy, wherein the metabolites as defined in anyone of the embodiments 3 to 19;
      2. b) at least one standard or control panel of low molecular early metabolic markers indicative of non-injured brain, and/or at least one standard or control panel of low molecular early metabolic markers indicative of a certain state of progression or regression of neonatal encephalopathy ; and
      3. c) means for identifying the disease state based on a comparison of the metabolite panel of the patient and the standard panel.
  • In particular the claimed analytical methods are performed in vitro
  • c) Further embodiments of the invention
  • Further aspects of the present invention are described below. In particular, by following the general teaching of the present invention at least the following additional embodiments are available to skilled reader.
  • c1) Diagnostic applications
  • In some embodiments, the present invention provides methods and compositions for
    • diagnosing brain injury affecting basal ganglia, hippocampus or other distinct brain tissues in infants and diagnosing adverse neurological outcome in infants,
    • characterising the risk of brain injury in basal ganglia, hippocampus or other distinct brain tissues in infants and the risk of adverse neurological outcome in infants,
    • diagnosing the stage of brain injury in basal ganglia, hippocampus or other distinct brain tissues in infants and severity etc. based on the presence of brain injury-specific endogenous metabolites or their chemical derivatives, precursors, metabolites, etc.
  • Exemplary diagnostic methods are described below.
  • Thus, for example, a method of diagnosing (or aiding in diagnosing) whether a subject has NE comprises detecting the presence or absence or a differential level of a plurality of metabolites being specific for brain injury in basal ganglia, hippocampus or other distinct brain tissues in infants or specific for adverse neurological outcome in infants and diagnosing brain injury in basal ganglia, hippocampus or other distinct brain tissues in infants or adverse neurological outcome in infants based on the presence, absence or differential concentration levels of these compounds. The presence, absence or concentration changes of these endogenous metabolites is used for differentiation of damaged brain regions and damaged brain tissues. Such specific metabolites are selected from Tables 2, 3 or 4.
  • In some embodiments, a computer-based analysis program is used to translate the raw data generated by the detection assay (e.g., the presence, absence, or amount of a NE specific metabolite) into data of predictive value for a clinician. The clinician can access the predictive data using any suitable means. Thus, in some embodiments, the present invention provides the further benefit that the clinician, who is not likely to be trained in metabolite analysis, need not understand the raw data. The data is presented directly to the clinician in its most useful form. The clinician is then able to immediately utilise the information in order to optimise the care of the subject.
  • The present invention contemplates any method capable of receiving, processing, and transmitting the information to and from laboratories conducting the assays, information providers, medical personal, and subjects. The profile data is then prepared in a format suitable for interpretation by a treating clinician. For example, rather than providing raw data, the prepared format may represent a diagnosis or risk assessment (e.g., likelihood of NE in infants being present) for the subject, along with recommendations for particular treatment options. The data may be displayed to the clinician by any suitable method. For example, in some embodiments, the profiling service generates a report that can be printed for the clinician (e.g., at the point of care) or displayed to the clinician on a computer monitor.
  • In some embodiments, the information is first analysed at the point of care or at a regional facility. The raw data is then sent to a central processing facility for further analysis and/or to convert the raw data to information useful for a clinician or patient. The central processing facility provides the advantage of privacy (all data is stored in a central facility with uniform security protocols), speed, and uniformity of data analysis. The central processing facility can then control the fate of the data following treatment of the subject. For example, using an electronic communication system, the central facility can provide data to the clinician, the subject, or researchers.
  • When the amounts or levels of a plurality of metabolites in the sample are determined, the amounts or levels may be compared to NE metabolite-reference levels, such as NE in infants-positive and/or NE in infants-negative reference levels to aid in diagnosing or to diagnose whether the subject has NE. Levels of the plurality of metabolites in a sample corresponding to the NE in infants-positive reference levels (e.g., levels that are the same as the reference levels, substantially the same as the reference levels, above and/or below the minimum and/or maximum of the reference levels, and/or within the range of the reference levels) are indicative of a diagnosis of NE in infants in the subject.
  • In addition, levels of a plurality metabolites that are differentially present (especially at a level that is statistically significant) in the sample as compared to NE in infants-negative reference levels are indicative of a diagnosis of NE in the subject. Levels of the two or more metabolites that are differentially present (especially at a level that is statistically significant) in the sample as compared to NE-positive respectively brain injury in a distinct brain tissue positive reference levels are indicative of a diagnosis of no brain injury in infants in the subject.
  • The level(s) of a plurality of the metabolites may be compared to NE in infants -positive respectively brain injury in a distinct brain tissue positive and/or NE -negative reference levels using various techniques, including a simple comparison (e.g., a manual comparison) of the level(s) of the one or more metabolites in the biological sample to NE -positive and/or NE -negative reference levels. The level(s) of the one or more metabolites in the biological sample may also be compared to NE in infants-positive respectively brain injury in a distinct brain tissue positive and/or brain injury in infants - negative reference levels using one or more statistical analyses (e.g., linear models, t-test, logistic regression, Wilcoxon's rank sum test, decision tree, linear discriminant analysis, k nearest neighbours etc.).
  • Embodiments of the present invention provide for multiplex or panel assays that simultaneously detect a plurality (at least two) of the markers of the present invention depicted in table 1, 2, 3 or 4. For example, in some embodiments, panel or combination assays are provided that detected 2 or more, 3 or more, 4 or more, 5 or more, 6 or more, 7 or more, 8 or more, 9 or more, 10 or more, 5 or more markers in a single assay. Non-limiting examples of panels are given in Tables 8, 9, 10, 11, 12 or 13. In some embodiments, assays are automated or high-throughput.
  • In the following non-limiting examples of particular diagnostic applications of the diagnostic principal method of the invention are given:
    • Thus, for example, the present invention provides a method for predicting the likelihood of NE in infants, characterised by
      in vitro detecting, in particular quantitatively, in at least one biological sample of a neonate patient a plurality of, like 2, 3, 4, 5, 6, 7, 8, 9 or 10, compounds being associated with, in particular specific for NE, and having a molecular weight of less than about 1500 Dalton (like in the range of 50 to 1500), which method comprises the steps of:
      1. a) selecting said compounds from a group of endogenous metabolites as defined in anyone of the above tables 2 and 3;
      2. b) measuring at least two, like 2, 3, 4 or 5, of the parameters selected from the group consisting of: concentration, level or amount of each specific compound of said plurality of compounds in said sample, qualitative and/or quantitative molecular pattern and/or molecular signature; and storing the obtained set of values in a database;
      3. c) calibrating said values, as for example by comparing clinically confirmed "NE in infants-positive" by assignment of NE to distinct brain tissues and/or clinically confirmed "NE in infants-negative" reference parameters;
      4. d) comparing said measured values in the sample with the calibrated values, in order to assess whether the neonate patient has or is likely to develop NE or is unlikely to develop NE.
    The levels of one or more of the recited metabolites may be determined in the methods of the present invention. For example, the level(s) of one metabolite, two or more metabolites, three or more metabolites, four or more metabolites, five or more metabolites, six or more metabolites, seven or more metabolites, eight or more metabolites, nine or more metabolites, ten or more metabolites, etc., including a combination of some or all of the metabolites including, but not limited to those listed in Table 2 and Table 3, may be determined and used in such methods.
  • The present invention also relates to a method for predicting neurological outcome due to NE in infants characterized by
    in vitro detecting, in particular quantitatively, in at least one biological sample of a neonate patient a plurality of, like 2, 3, 4, 5, 6, 7, 8, 9 or 10, compounds being associated with, in particular specific for NE, and having a molecular weight of less than about 1500 Dalton (like in the range of 50 to 1500), comprising the steps of:
    1. a) selecting said compounds from a group of endogenous metabolites as defined in above Table 4;
    2. b) measuring at least two, like 2, 3, 4 or 5, of the parameters selected from the group consisting of: concentration, level or amount of each specific compound of said plurality of compounds in said sample, qualitative and/or quantitative molecular pattern and/or molecular signature; and storing the obtained set of values in a database;
    3. c) calibrating said values, as for example by comparing clinically confirmed "NE in infants-positive" with neurological behavioural evaluation and/or clinically confirmed "NE in infants-negative" reference parameters;
    4. d) comparing said measured values in the sample with the calibrated values, in order to assess brain-damage related neurological outcome of the neonate.
  • The levels of one or more of the recited metabolites may be determined in the methods of the present invention. For example, the level(s) of one metabolites, two or more metabolites, three or more metabolites, four or more metabolites, five or more metabolites, six or more metabolites, seven or more metabolites, eight or more metabolites, nine or more metabolites, ten or more metabolites, etc., including a combination of some or all of the metabolites including, but not limited to those listed in Table 4, may be determined and used in such methods.
  • Determining levels of combinations of the metabolites may allow greater sensitivity and specificity in the methods, such as diagnosing NE related to brain damage of basal ganglia and or hippocampus or for determining neurological outcome and aiding in the diagnosis of NE, and may allow better differentiation or characterisation of NE due to damage of distinct brain tissues from other disorders that may have similar or overlapping metabolites to NE due to damage of distinct brain tissues such as - but not limited to - basal ganglia and or hippocampus (as compared to a subject not having brain damage or having brain damage due to damage of other brain tissues). Determining levels of combinations of the metabolites may also allow greater sensitivity and specificity in the methods for determining neurological outcome.
  • Accordingly, the present invention provides, inter alia, methods of predicting the extent of brain damage and therefore the likelihood of an onset of NE together with an identification of damaged brain tissues such as - but not limited to - hippocampus tissue and or basal ganglia in an individual. The invention further provides methods for predicting the neurological outcome due to brain damage and therefore the likelihood of NE.
  • The methods of the invention may also comprise obtaining a biomarker score at a single point of time from the individual and comparing the individual's biomarker profile to a reference biomarker profile. Comparison of the biomarker profiles can predict the onset of NE in the individual preferably with an accuracy of at least about 75%. This method may be repeated again at any time prior to the onset of NE in infants.
  • Additionally, the present invention provides a method of diagnosing NE in infants related to damage of distinct brain tissues such as - but not limited to - hippocampus and or basal ganglia -in an individual having or suspected of having NE in infants. This method comprises obtaining a biomarker score (as for example selected from the scores or models as listed in the attached tables 8, 9, 11 or 12) at a single point in time from the individual and comparing the individual's biomarker score to a reference biomarker score. Comparison of the biomarker profiles can diagnose NE in infants in the individual with an accuracy of at least about 75 %. This method may also be repeated on the individual at any time.
  • The present invention further provides a method of determining the progression (i.e., the stage) of NE involving distinct brain tissues such as, but not limited to, basal ganglia and or hippocampus in an individual. This method comprises obtaining a biomarker profile composed of concentrations of metabolites (two or more) selected from Tables 2 or 3 (or selected from the scores or models as listed in the attached tables 8, 9, 11 or 12) at a single point in time from the individual and comparing the individual's biomarker profile to a reference biomarker score. Comparison of the biomarker scores can determine the progression of NE related to damaged brain tissues in individual infants preferably with an accuracy of at least about 75%. This method may also be repeated on the individual at any time.
  • In yet another embodiment, the present invention provides, inter alia, a method of determining the status of NE in infants or diagnosing NE related to damage of distinct brain areas in infants. The method comprises comparing a measurable characteristic of more than one metabolite of a metabolite biomarker panel or biomarker score composed of (processed or unprocessed) values of this panel obtained from a biological sample from the individual infant and a biomarker score obtained from biological samples from a reference population. Based on this comparison, the individual is classified as belonging to or not belonging to the reference population. The comparison, therefore, determines the likelihood of NE in infants due to likely damage of distinct brain tissues or diagnoses of such NE in infants in the individual. The biomarkers, in one embodiment, are selected from the list of metabolites shown in Tables 2 or 3 or, for example, are selected from the scores or models as listed in the attached tables 8, 9, 11 or 12 .
  • The present invention also provides methods for predicting NE related to damage of hippocampus and or basal ganglia tissue in infants. Such methods comprise the steps of: analyzing a biological sample from a subject to determine the levels of more than one metabolites for NE in infants in the sample, where the one or more metabolites are selected from Tables 2 and 3 (or are, for example, selected from the scores or models as listed in the attached tables 8, 9, 11 or 12) and comparing the levels of the metabolites, as well as a composed value / score generated by subjecting the concentrations of individual metabolite in the sample to a classification method such as affording an equation to process single concentration values - to obtain a separation between both (diseased and healthy) groups or comparing the level(s) of the one or more metabolites in the sample to NE positive or NE negative reference levels of the two or more metabolites in order to determine whether the subject is developing NE related to damage of hippocampus, basal ganglia or other distinct brain tissues.
  • The above methods for determining progression, status of disease or predicting disease may also be applied to the aspect of the invention related to neurological behavioural damages or deficits. For these purposes one or more metabolites as listed in Table 4 or one or more metabolite combinations listed in Table 10 or 13 may be applied accordingly.
  • Furthermore, in some embodiments, the present invention provides a method of diagnosing brain damage in infants and/or duration/severity of brain damage of distinct brain areas, identification of affected area(s) of NE and risk of neonatal encephalopathy and prognosis and neurological outcome due to identification of type and extent of damage of distinct brain tissues, in particular of hippocampus and / or basal ganglia comprising: detecting (the presence or absence of 2 or more, 3 or more, 5 or more, 10 or more, etc. metabolites measured together in a multiplex or panel format) brain damage in infants specific metabolites in a sample (e.g., a tissue (e.g., biopsy) sample, a blood sample, a serum sample) from a subject; and diagnosing brain damage in the aforementioned brain tissues in infants based on the presence of specific metabolites.
  • In a further embodiment the invention uses analytical kits, comprising
    1. i) detection agents for the determination of NE in infants by determination of concentrations of metabolites of the subject, wherein said metabolites are selected from the group consisting of hippocampus specific compounds as listed in Table 2, above, , basal ganglia-specific compounds as listed in Table 3, above or neurological behavioural score-specific compounds as listed in table 4, or detecting agents for hippocampus specific, basal ganglia-specific or neurological behavioural score-specific sets of such metabolites from compounds of tables 2, 3 or 4, as for example sets of metabolites as defined in any one of the tables 8 to 13;.
    2. ii) positive and/or negative controls; and
    3. iii) regression software for correlating the results achieved with said detection agents.
    c2) Further particular aspects for performing the methods of the invention
  • The present invention provides a solution to the problems described above, and generally relates to the use of metabolomics data, generated by quantization of endogenous metabolites by but not limited to mass spectrometry (MS), in particular MS-technologies such as MALDI, ESI, atmospheric pressure chemical ionization (APCI), and other methods, determination of metabolite concentrations by use of MS-technologies or alternative methods coupled to separation (LC-MS, GC-MS, CE-MS), subsequent feature selection and combination of features to classifiers including molecular data of at least two molecules.
  • The concentrations of the individual markers, analytes, metabolites thus are measured and compared to reference values or data combined and processed to scores and compared to reference values thus indicating diseased states etc. with superior sensitivities and specificities compared to known procedures, clinical parameters and biomarkers.
  • Those skilled in the art will understand that for the quantitation of certain metabolites, also chemically modified metabolites may be used as one may get a better separation on the column material used prior to the MS-technologies.
  • Typically analysed samples are e.g., a tissue (e.g., biopsy) sample, a blood sample, a serum sample, from a subject.
  • In a preferred embodiment of the invention, the analytical procedure is also characterized in that a deproteinization step and/or a separation step is performed before metabolite measurement, wherein said separation step is selected from the group consisting of liquid chromatography (LC), high performance liquid chromatography (HPLC), gas chromatography, liquid-liquid-extraction (LLE).
  • Said deproteinization step preferably is carried out by mixing said biological sample with organic solvents such as ethanol, methanol or acetonitrile.
  • In order to enhance sensitivity and/or volatility, e.g. for a better evaporation as used in mass spectrometry, the compounds can be derivatized. They may be converted, py applying chemical methods known in the art, to the corresponding esters, amines or amides, wherein said derivatization includes: 2-Hydrazinopyridine (HP), 2-picolylamine (PA); Girard derivatization; oximation with hydroxylamine first and then silylation with hexamethyldisilazane and trifluoroacetic acid.
  • It is further preferred that said calibration step is carried out by
    1. a) mathematically preprocessing said values in order to reduce technical errors being inherent to the measuring procedures used in accordance with the present invention, such as mass spectrometry.
    2. b) selecting at least one suitable supervised algorithm from the group consisting of logistic regression, (diagonal) linear or quadratic discriminant analysis (LDA, QDA, DLDA, DQDA), perceptron, shrunken centroids regularized discriminant analysis (RDA), random forests (RF), neural networks (NN), Bayesian networks, hidden Markov models, support vector machines (SVM), generalized partial least squares (GPLS), partitioning around medoids (PAM), inductive logic programming (ILP), generalized additive models, gaussian processes, regularized least square regression, self organizing maps (SOM), recursive partitioning and regression trees, K-nearest neighbor classifiers (K-NN), and applying said selected supervisedalgorithm to said preprocessed data of step a);
    3. c) said supervised algorithm of step b) being trained on at least one training data set containing preprocessed data from subjects being divided into classes according to their NE in infants-related pathophysiological, physiological, prognostic, or responder conditions, in order to select a classifier function to map said preprocessed data to said conditions;
    4. d) applying said trained supervised algorithm of step c) to a pre-processed data set of a subject with unknown NE in infants-related pathophysiological, physiological, prognostic, or responder condition, and using the trained classifier algorithms to predict the class label of said data set in order to predict the likelihood of an onset of NE in infants of the subject.
  • The step of mathematically preprocessing can be carried out e.g. by means of a statistical method on obtained raw data, particularly raw intensity data obtained by a measuring device, wherein said statistical method is selected from the group consisting of raw data obtained by mass spectrometry or mass spectrometry coupled to liquid or gas chromatography or capillary electrophoresis or by 2D gel electrophoresis, quantitative determination with RIA or determination of concentrations/amounts by quantitation of immunoblots; smoothing, baseline correction, peak picking, optionally, additional further data transformation such as taking the logarithm in order to carry out a stabilization of the variances.
  • Furthermore, for reasons of better accuracy of the prognostic results, a further step of feature selection is inserted into said preprocessing step, in order to find a lower dimensional subset of features with the highest discriminatory power between classes; and/or said feature selection is carried out by a filter and/or a wrapper approach; and/or wherein said filter approach includes rankers and/or feature subset evaluation methods; and/or wherein said wrapper approach is applied, where a classifier is used to evaluate attribute subsets.
  • For the purpose of the present application, said pathophysiological condition corresponds to the label " diseased" and said physiological condition corresponds to the label " healthy" or said pathophysiological condition corresponds to different labels of " grades of a disease" , " subtypes of a disease" , different values of a "score for a defined disease" ; said prognostic condition corresponds to a label " good" , " medium" , " poor" , or " therapeutically responding" or "therapeutically non-responding" or "therapeutically poor responding".
  • Typically, the method of the present invention is characterised in that said measuring step is carried out by high-throughput mass spectrometry.
  • It is preferred, that said NE in infants specific endogenous compounds indicate neonatal encephalopathy, NE of affected brain area(s) and prognosis and neurological outcome due to determination of type and extent of damage of distinct brain tissues, in particular of hippocampus and / or basal ganglia in infants specific endogenous metabolites.
  • Furthermore, in the method according to the present invention, typically, said mammalian subject is a human being, and said biological sample is blood wherein raw data of metabolite concentrations are preprocessed using the log transformation; wherein linear models are used to identify metabolites which are correlated to the extend of NE present; wherein least square regression is selected as suitable supervised algorithm, and is trained with preprocessed metabolite concentrations, applying the obtained trained regression function to said pre-processed metabolite concentration data set of a subject under suspicion of having NE in infants, and using said trained regression function to diagnose or predict the extent of brain tissue-specific injury in infants.
  • The present invention allows prognosis of NE-related neurological outcome and neurological behavioural score by metabolites of the subject (with or without determination of type and extent of damage of distinct brain tissues, in particular of hippocampus and / or basal ganglia in infants specific endogenous metabolites) wherein linear models are used to identify metabolites which are differentially present; wherein linear least squares regression is selected as suitable algorithm to delineate a relationship between metabolite and extent of damage, and is trained with preprocessed metabolite concentrations, applying the obtained trained regression function to said preprocessed metabolite concentration data set of a subject under suspicion of having NE in infants, and using said trained regression to diagnose or predict the extend of brain tissue-specific injury in infants.
  • In a further embodiment, categorization of data relies on the application of (un-) supervised learning techniques. Supervised learning algorithms are typically deterministic functions that map a multi-dimensional vector of biological measurements to a binary or n-ary or continuous outcome variable that encodes the absence or existence of a clinically-relevant class, phenotype, distinct physiological state or distinct state of disease or risk of developing a disease or disease treatment adequacy. To achieve these various methods such as, but not limited to, logistic regression (LR), (diagonal) linear or quadratic discriminant analysis (LDA, QDA, DLDA, DQDA), perceptron, shrunken centroids regularized discriminant analysis (RDA), random forests (RF), neural networks (NN), support vector machine (SVM), generalised least square regression, (non-)linear mixed-effects models, generalised (non-)linear models, mixed hidden Markov models, generalised partial least square regression (GPLS), principal component regression, partial least square regression coupled with a classification algorithm (such as LDA, K-NN or LR), projection to latent structures, partitioning around medoids (PAM), naïve Bayes (NB), inductive logic programming (ILP), generalized additive models, gaussian processes, regularized least square regression, least absolute deviations, self organizing maps (SOM), recursive partitioning and regression trees, K-nearest neighbour classifiers (K-NN), fuzzy classifiers can be used as a standalone classifer or within the framework of ensemble strategy such as voting, stacking, Bayseian model averaging, bagging or boosting.
  • EXAMPLES
  • The following examples are provided in order to further illustrate certain preferred embodiments of the present invention and are not to be construed as limiting the scope thereof.
  • I. MATERIAL AND METHODS 1. Animal model
  • When comparing brain growth spurts, the brain of the pig resembles most that of the term born human baby (see Dobbing J, Sands J. Comparative aspects of the brain growth spurt. Early Hum Dev 1979 Mar;3(1):79-83).
  • In this study we chose the inhalational hypoxia model since it mimicks the human pathophysiology of a global hypoxic ischemic insult and produces spontaneous clinical and subclinical seizures, but with a high survival rate (∼80%). The encephalopathy is clinically, electrophysiologically, and neuropathologically similar to that in the asphyxiated term infant and is suitable for examining mechanisms of damage and evaluation of potential protective therapies after birth asphyxia (see Thoresen M, Haaland K, Loberg EM, Whitelaw A, Apricena F, Hanko E, et al. A piglet survival model of posthypoxic encephalopathy. Pediatr Res 1996 Nov;40(5):738-48).
  • The animals were bred in a piggery in Brisbane. After ventilation and detubation piglets stayed in a small animal cage with liberate access to water. Piglets were bottlefed every 3-4 hours with Survive Pig Milk Replacer (Think Pig-Country Vet Wholesaling Pty Ltd, VIC, Australia). Animals were cared for in accordance with the institution' s guidelines for experimental animals. All experiments were approved by the animal protection committee of the local authorities.
  • 9 newborn piglets were used for this study. Piglets were anaesthetized with 1-2% isofluran via a nose mask, and placed supine on a heating table to maintain body temperature around 38,5°C. An ear vein was cannulated and an induction dose of propofol (10 mg/ml, 0.5 ml/kg Diprivan 1 %, AstraZeneca Pty Ltd, NSW, Australia) was administered. Propofol (9mg/ml) and alfentanil infusion was maintained at a rate of 10 mg/kg/hr until intubation. Pulse oximeter and ECG (Marquette Tramscope 12C, Medical Systems, WI, USA) was connected as well as the amplitude-integrated EEG (BRM2; BrainZ Instruments, Auckland, NZ). piglets were intubated with an uncuffed tube and pigs were ventilated pressure-controlled with an SLE Newborn 250 (Surrey, UK). Anesthesia was reduced to 10 mg/kg/hr until the end of HI. An additional peripheral venous line was inserted for continuous 10% dextrose infusion at a rate of 3 ml/kg/hr and antibiotics (cephalotin 20 mg/kg and gentamicine 2.5 mg/kg). An umbilical artery was inserted for continuous blood pressure monitoring and blood gas analysis. Blood gasses were collected before HI, every 10 minutes during HI until 60 min after HI.
  • Hypoxia (4% O2) was induced in anaesthetised newborn piglets for 30 min with a final 10 min period of hypotension; piglets were recovered and survived to 48h. Animals were monitored daily for seizures both visually and with electroencephalogram (EEG) recordings. Clinical seizures were treated with phenobarbitone (20 mg/kg i.v., Sigma, Croydan, VIC, Australia) and midazolam (0,2 mg/kg iv, Sandoz, Pyrmont, NSW, Australia). When seizures continued, piglets were euthanized with an overdose pentobarbitone.
  • For metabolomic analysis, blood samples were taken at the following time points: 30 min after asphyxia and 21 hours after resuscitation.
  • Outcome measures:
  • Brain injury was assessed with the aEEG for both EEG pattern and epileptic activity, with a clinical neurological score, by histology (haematoxylin and eosin staining) using a previously described rating system (see Lorek A, Takei Y, Cady EB, Wyatt JS, Penrice J, Edwards AD, et al. Delayed ("secondary") cerebral energy failure after acute hypoxiaischemia in the newborn piglet: continuous 48-hour studies by phosphorus magnetic resonance spectroscopy. Pediatr Res 1994 Dec;36(6):699-706) and for caspase-3 activity in 4 cortical areas, thalamus, basal ganglia and hippocampus. Thereby the hippocampus and basal ganglia are of outmost interest.
  • Caspase-3 activity:
  • Caspase 3-activity (in pmole/min/mg protein) was determined at 48h after HI in all other brain regions, including 4 cortical areas, basal ganglia and hippocampus.
  • Histology:
  • Histology was performed using the earlier described score in each brain region. Also a total histology score was calculated for each treatment group, summing all the individual histology scores.
  • Clinical neurobehavioural score:
  • A neurobehavioral score was assessed at least at 4 hourly time points in the first 24h and at 48h. This score contains 9 items of maximal 2 points, so the maximal score is 18 points. The nine neurologic items were scored as: 2, normal; 1, moderately abnormal; or 0, definitely pathologic. Neurologic items were: 1) Normal respiration, without apnea, retractions, or need for oxygen; 2) consciousness; 3) orientation. Looking at and investigating the surroundings; 4) ability to walk on all four limbs in one direction without falling;5) ability to control the forelimbs using them to raise quickly from a lying position; 6) ability to control the hind limbs using them to raise quickly from a lying position and keeping them together in the upright position; 7) maintenance of steady and equal tone in forelimbs and hind limbs; 8) almost continuous activity when awake; 9) absence of pathologic movements were scored as 2. Sustained clonic movements or persistent tonic postures were scored as 0. Occasional cycling movements or jerks were scored as 1.
  • 2. Metabolomic Analytics: 2.1 General
  • Sample preparation and metabolomic analyses were performed at Biocrates life sciences AG, Innsbruck, Austria. We used a multi-parametric, highly robust, sensitive and high-throughput targeted metabolomic platform consisting of flow injection analysis (FIA)-MS/MS and LC-MS/MS methods for the simultaneous quantification of a broad range of endogenous intermediates, namely acylcarnitines, sphingomyelins, hexoses, glycerophospholipids, amino acids, biogenic amines, oxysterols and small organic acids, in plasma. A detailed list of all analyzed metabolites is depicted in Table 1, above. All procedures (sample handling, analytics) were performed by co-workers blinded to the experimental groups.
  • 2.2. Sample handling 2.2.1 Plasma
  • Plasma samples were prepared by standard procedures and stored at (-75°C). To enable analysis of all samples simultaneously within one batch, samples were thawed on ice (1 h) on the day of analysis and centrifuged at 18000g at 2°C for 5 min. All tubes were prepared with 0.001 % BHT (butylated hydroxytoluene; Sigma-Aldrich, Vienna, Austria) to prevent autoxidation.
  • 2.2.2 LC-MS/MS system
  • The LC-MS/MS system consisted of an API 5000™ triple quadrupole mass spectrometer (AB Sciex) equipped with a Turbo V™ ESI source and an Agilent 1200 HPLC system (Agilent Technologies). Chromatographic separation was performed using an Agilent Zorbax Eclipse XDB C18 column (100 x 3.0 mm, 3.5 µm) with guard column (C 18, 4 x 2 mm in Security Guard Cartridge, Phenomenex). Analyst™ software (version 1.4.2, Applied Biosystems) was used for data acquisition and processing. For comprehensive statistical analysis the data were exported.
  • 2.2.3 LC-MS/MS conditions
  • The ESI source was operated in negative ion mode and an ion-spray voltage of -3 kV was applied. Heater temperature was set at 400 °C.
  • 2.3. Mass spectroscopy of different analytes 2.3.1 Acylcarnitines, Sphingomyelins, Hexoses, Glycerophospholipids (FIA-MS/MS)
  • To determine the concentration of acylcarnitines, sphingomyelins and glycerophospholipids in plasma, the AbsoluteIDQ kit p150 (Biocrates Life Sciences AG, Innsbruck, Austria) was prepared as described in the manufacturer' s protocol. In brief, 10 µL of plasma was added to the center of the filter on the upper 96-well kit plate and was dried using a nitrogen evaporator (VLM Laboratories, Bielefeld, Germany). Subsequently, 20 µL of a 5% solution of phenyl-isothiocyanate was added for derivatization. After incubation, the filter spots were dried again using an evaporator. The metabolites were extracted using 300 µL of a 5 mM ammonium acetate solution in methanol. The extracts were obtained by centrifugation into the lower 96-deep well plate, followed by a dilution step with 600 µL of kit MS running solvent. Mass spectrometric analysis was performed on an API4000 Qtrap® tandem mass spectrometry instrument (Applied Biosystems/MDS Analytical Technologies, Foster City, CA) equipped with an electro-spray ionization (ESI)-source, using the analysis acquisition method as provided in the AbsoluteIDQ kit. The standard FIA-MS/MS method was applied for all measurements with two subsequent 20-µL injections (one for positive and one for negative mode analysis). Multiple reaction monitoring (MRM) detection was used for quantification, applying the spectra parsing algorithm integrated into the MetIQ software (Biocrates Life Sciences AG, Innsbruck, Austria). The concentrations for 148 metabolites (all analytes were determined with the metabolomics kit except for the amino acids, which were determined by a different method) obtained by internal calibration were exported for comprehensive statistical analysis.
  • 2.3.2 Amino acids, Biogenic amines (LC-MS/MS)
  • Amino acids and biogenic amines were quantitatively analyzed by reversed phase LC-MS/MS to obtain the chromatographic separation of isobaric (same MRM ion pairs) metabolites for individual quantification performed by external calibration and by use of internal standards. A 10 µL sample volume is required for the analysis using the following sample preparation procedure. Samples were added on filter spots placed in a 96- solvinert well plate (internal standards were placed and dried down under nitrogen before), fixed above a 96 deep well plate (capture plate). 20 µL of 5% phenyl-isothiocyanate derivatization reagent was added. The derivative samples were extracted after incubation by aqueous methanol into the capture plate. Sample extracts were analyzed by LC-ESI-MS/MS in positive MRM detection mode with an API4000 Qtrap® tandem mass spectrometry instrument (Applied Biosystems/MDS Analytical Technologies, Foster City, CA). The analyzed individual metabolite concentrations (Analyst 1.4.2 software, Applied Biosystems, Foster City, CA) were exported for comprehensive statistical analysis.
  • 2.3.3 Oxysterols (LC-MS/MS)
  • Oxysterols were quantitatively analyzed by reversed phase LC-ESI-MS/MS to realize liquid chromatographic separation and thus individual quantification of isobaric oxysterols. The most selective detection was performed in positive MRM detection mode using a 4000 Qtrap® tandem mass spectrometry instrument (Applied Biosystems/MDS Analytical Technologies, Foster City, CA). Data were quantified with Analyst 1.4.2 software (Applied Biosystems, Foster City, CA). Ratios of external to internal standards were applied for quantification by means of external 6-point calibration. A sample volume of 20 µL (plasma) was necessary for the analysis. The sample preparation included: I) protein precipitation by placing a 20 µL sample volume on the filter spot, and precipitation by 200 µL Naïve; II) hydrolysis by 100 µL of 0.35 M KOH in 95% ethanol for 2 hrs; III) a washing step (3x200 µL H2O) to remove hydrolysis reagent; and, finally, IV) extraction by means of 100 µL aqueous methanol. The 20 µL sample extracts were analyzed by the developed LC-ESI-MS/MS method.
  • 2.3.4 Energy metabolism (Organic Acids) (LC-MS/MS)
  • For the quantitative analysis of energy metabolism intermediates (glycolysis, citrate cycle, pentose phosphate pathway, urea cycle), a hydrophilic interaction liquid chromatography (HILIC)-ESI-MS/MS method in a highly selective negative MRM detection mode was used. The MRM detection was performed using an API4000 QTrap® tandem mass spectrometry instrument (Applied Biosystems/MDS Analytical Technologies, Foster City, CA). A 20 µL sample volume (plasma) was proteinprecipitated and simultaneously extracted with aqueous methanol in a 96-well plate format. Internal standards (ratio external to internal standard) and external calibration were used for highly accurate quantification. Data were quantified with Analyst 1.4.2 software (Applied Biosystems, Foster City, CA) and finally exported for statistical analysis.
  • 2.3.5 Eicosanoids
  • The determination of eicosanoids (like prostaglanidins, thromboxanes) was performed according to a previously published method (Unterwurzacher I., Koal T., Bonn G.K., Weinberger K.M., Ramsay S.L., Clin Chem Lab Med 2008, 46(11), 1589). In brief, 20 µL of plasma was protein precipitated and extracted simultaneouly with aqueous acetonitrile in a 96-well Solvinert filter plate. The ratio of external to internal standard and external calibration were used for highly accurate quantitation. Sample extracts were analyzed by reversed phase LC-ESI-MS/MS in negative ionization MRM detection mode with a 4000 Q Trap® tandem mass spectrometry instrument (Applied Biosystems/MDS Analytical Technologies, Darmstadt, Germany).
  • 2.4. Statistical Analysis
  • All statistical calculations have been performed using the statistics software R (R: A Language and Environment for Statistical Computing, R Development Core Team, R Foundation for Statistical Computing, Vienna, Austria, 2010, ISBN 3-900051-07-0).
  • All analytes that were detected in at least 15% of the samples were selected for further analyses. The metabolic data is left censored due to thresholding of the mass spectrometer data resulting in non detected peak/signals. By a combination of metabolic pathway dynamism, complex sample molecular interaction and overall efficiency of the analytical protocol, replacement of missing data by means of a multivariate algorithm is preferred to a naive imputation by a pre-specified value like for instance zero. Hence, missing metabolite concentrations are replaced by the average value of the 6 closest samples to the one where the measurement is missing (Kim H., Golub G.H. and Park, H. Missing value estimation for DNA microarray gene expression data: local least squares imputation. Bioinformatics. 2005 21 (2):187-198). All statistical analyses are performed on preprocessed - that is, log transformed - data. The logtransformation is used to stabilize variance and to transform to Gaussian distribution - at least approximately.
  • Parsimonious multi-metabolite panels can be used for predicting each outcome described in the present invention rather than individual metabolite marker. Approach to search for marker composites is done using a population-based incremental learning algorithm using all 101 metabolites. For each model, regression coefficient (i.e. marker weights in the model) are determined according to Zuber, V., & Strimmer, K. (High-Dimensional Regression and Variable Selection Using CAR Scores, Statistical Applications in Genetics and Molecular Biology. 2011 10(1), Article 34). Predictive power of the model is assessed by leave one out cross-validation. In the following, model accuracy is defined as the correlation coefficient between the original (or true) values of the predictand and their predicted values by resampling. Each model is then further subjected to backward elimination and this until no improvement to the accuracy (plus/minus 10%) is observed. All together, these conditions satisfy parsimony and predictive power of the final model, and eliminate issues related to multicollinearity between markers. While the invention described herein may comprise combinations with adequate predictive power other than those shown, combination of metabolites of the invention would exhibit accuracies greater than 80%.
  • II. EXPERIMENTAL RESULTS
  • Induced asphyxia resulted in different grades of brain injury by inducing cell death in basal ganglia and hippocampus as well as by a deterioration of the neurological behavioural score. Neonatal encephalopathy was associated with major changes in the plasma metabolome. We discovered intermediates which correlated alone or in combination with the extent of brain injury in the hippocampus, basal ganglia and the neurological score.
  • These experimental results are explained in more detail below.
  • Example 1: Hypoxia-induced damage of hippocampus
  • As mentioned above the lack oxygen resulted in increased apoptotic and/or necrotic cell death assessed in the brain of newborn piglets 48 hours after the lack of oxygen. Blood samples were taken 30 minutes after the period of lack of oxygen and the metabolite concentrations were analysed as described above. These metabolite concentrations were then correlated with the absolute quantitative amount of dying cell in the hippocampus. Table 5 summarises the result of univariate correlation statistics between metabolite concentration as determined in plasma 30 minutes after asphyxia and the amount of cell death in hippocampus at 48 hours after asphyxia. For each metabolite, Pearson correlation coefficient (Cor) and its corresponding p value are given alongside the coefficient of determination (Rsq). Prob designates the actual probability (in %) to enter a combination of metabolites. Table 5. Outcome parameter: Brain damage in hippocampus
    Short Full name Cor Pvalue Rsq Prob
    1 Lac Lactate 0,870 0,002 75,69 61,38
    2 Fum Fumaric acid 0,753 0,019 56,63 43,45
    3 Ac-Orn N-acetylornithine 0,747 0,021 55,73 40,69
    4 Carnosine Carnosine -0,741 0,022 54,96 27,59
    5 C5:1-DC Glutaconylcarnitine / Mesaconylcarnitine (Undecanoylcarnitine) 0,666 0,050 44,35 20,00
    6 C16:2 Hexadecadienoylcarnitine 0,464 0,208 21,53 16,55
    7 Pent-P Pentosephosphate (e.g. Ribose-5-phosphate + Ribulose-5-phosphate) 0,651 0,057 42,40 13,79
    8 C10:2 Decadienoylcarnitine -0,485 0,186 23,51 13,10
    9 Met-SO Methionine-Sulfoxide 0,650 0,058 42,28 12,41
    10 SM (OH) C22:2 Hydroxysphingomyelin with acyl residue sum C22:2 -0,689 0,040 47,52 12,41
    11 SM C24:1 sphingomyelin with acyl residue sum C24:1 -0,586 0,098 34,29 11,72
    12 ADMA Asymmetric dimethylarginine 0,592 0,093 35,02 10,34
    13 C5:1 Tiglylcamitme / 3-Methyl-crotonylcarnitine -0,405 0,280 16,37 9,66
    14 3b,5a,6b-THC 3β,5α,6β-Trihydroxycholestan 0,290 0,449 8,40 8,28
    15 27-OH-C 27-Hydroxycholesterol 0,448 0,226 20,10 6,90
    16 Suc Succinic acid 0,533 0,139 28,41 6,90
    17 8-iso-PGF2a 8-iso-Prostaglandin F2alpha 0,525 0,147 27,52 6,21
    18 total DMA Total dimethylarginine 0,502 0,168 25,24 6,21
    19 25-OH-C 25-Hydroxycholesterol 0,229 0,553 5,25 5,52
    20 SM(OH)C22:1 Hydroxysphingomyelin with acyl residue sum C22:1 -0,495 0,176 24,46 4,14
    21 Creatinine Creatinine -0,344 0,364 11,85 3,45
    22 Phe Phenylalanine 0,648 0,059 41,95 3,45
    23 C4:1 Butenoylcarnitine -0,275 0,474 7,55 3,45
    24 LTB4 Leukotriene B4 0,449 0,225 20,18 2,76
    25 24S-OH-C 24-S-Hydroxycholesterol 0,239 0,536 5,72 2,76
    26 Om Ornithine 0,468 0,204 21,90 2,76
    27 Cit Citrulline -0,354 0,350 12,51 2,76
    28 SM (OH) C14:1 Hydroxysphingomyelin with acyl residue sum C14:1 -0,515 0,156 26,53 2,76
    29 H1 Hexoses -0,582 0,100 33,88 2,76
    30 C8:1 Octenoylcarnitine -0,307 0,422 9,41 2,76
    31 5a,6a-EpoxyC 5α,6α-Epoxycholesterol 0,222 0,567 4,91 2,07
    32 alpha-AAA 2-Aminoadipic acid 0,399 0,287 15,96 2,07
    33 Pro Proline 0,625 0,072 39,04 2,07
    34 Lys Lysine 0,466 0,206 21,76 2,07
    35 Arg Arginine 0,541 0,132 29,30 2,07
    36 SM C16:1 sphingomyelin with acyl residue sum C16:1 -0,389 0,301 15,13 2,07
    37 SDMA Symmetric dimethylarginine 0,247 0,521 6,12 1,38
    38 Met Methionine 0,513 0,158 26,35 1,38
    39 Gln Glutamine 0,213 0,582 4,55 1,38
    40 SM C26:1 sphingomyelin with acyl residue sum C26:1 -0,409 0,274 16,76 1,38
    41 SM C18:1 sphingomyelin with acyl residue sum C18:1 -0,621 0,074 38,52 1,38
    42 Hex-P Hexosephosphate (e.g. Glucose-1-phosphate + Glucose-6-phosphate + Fructose-6-phosphate) -0,526 0,146 27,69 1,38
  • In the attached Figure 1a, the distribution of accuracies that can be achieved with models formed with a lead metabolite is illustrated.
  • Figure 1 a illustrates the predictive abilities of the combination of metabolites based on a lead metabolite correlating with the extent of brain damage in the hippocampus. The box-and-whisker diagrams represent the distribution of the cross-validated correlation coefficient (y-axis) for combinations comprising a lead metabolite (x-axis) and up to 6 metabolites from the initial dataset.
  • In the attached Figure 1b, the distribution of the accuracies that can be achieved from models comprising up to 6 metabolites is illustrated.
  • Figure 1b illustrates the predictive abilities (i.e. accuracy) of all adequate metabolite combinations correlating with the extent of brain damage in the hippocampus. The box-and-whisker diagrams represent the distribution of the cross-validated correlation coefficient (y-axis) for combinations of 2 to 6 (x-axis) metabolites.
  • In the attached Figure 1c the probability of a metabolite to enter a model with adequate accuracy is illustrated.
  • Figure 1c illustrates the probabilities of single metabolites to enter a combination of metabolites correlating with cell death in the hippocampus. Probabilities are calculated over all models presented in Figure 1 b. Metabolites are sorted according to their likelihood to be included in a model and graphed back-to-back depending of their respective (i.e. positive or negative) contributions to the regression models. Left: metabolites inducing less damage in the hippocampus. Right: metabolites inducing more damage in the hippocampus.
  • Example 2: Hypoxia-induced damage of basal ganglia
  • As mentioned above the lack oxygen resulted in increased apoptotic and/or apoptotic cell death assessed in the brain of newborn piglets 48 hours after the lack of oxygen. Blood samples were taken 30 minutes after the period of lack of oxygen and the metabolite concentrations were analysed as described above. These metabolite concentrations were then correlated with the absolute quantitative amount of dying cell in the basal ganglia. Table 6 summarises the result of univariate correlation statistics between metabolite concentration as determined in plasma 30 minutes after asphyxia and the amount of cell death in basal ganglia at 48 hours after asphyxia. For each metabolite, Pearson correlation coefficient (Cor) and its corresponding p value are given alongside the coefficient of determination (Rsq). Prob designates the actual probability (in %) to enter a combination of metabolites. Table 6: Outcome parameter: Brain damage in Basal ganglia
    Short Full name Cor Value Rsq Prob
    1 Met Methionine 0,821 0,007 67,41 20,79
    2 SM (OH) C22:2 Hydroxysphingomyelin with acyl residue sum C22:2 -0,840 0,005 70,54 19,19
    3 SM (OH) C14:1 Hydroxysphingomyelin with acyl residue sum C14:1 -0,770 0,015 59,36 19,06
    4 Met-SO Methionine-Sulfoxide 0,774 0,014 59,97 18,63
    5 SM C16:1 sphingomyelin with acyl residue sum C16:1 -0,772 0,015 59,52 17,67
    6 SM (OH) C22:1 Hydroxysphingomyelin with acyl residue sum C22:1 -0,768 0,016 59,00 16,60
    7 Pro Proline 0,812 0,008 66,00 16,58
    8 Tyr Tyrosine 0,803 0,009 64,48 15,41
    9 Gln Glutamine 0,744 0,021 55,37 15,11
    10 SM C24:1 sphingomyelin with acyl residue sum C24:1 -0,805 0,009 64,75 14,52
    11 SM C24:0 sphingomyelin with acyl residue sum C24:0 -0,676 0,045 45,76 13,46
    12 SM C16:0 sphingomyelin with acyl residue sum C 16:0 -0,713 0,031 50,91 13,16
    13 Orn Ornithine 0,655 0,055 42,96 12,78
    14 Ac-Orn N-acetylornithine 0,699 0,036 48,86 11,76
    15 Arg Arginine 0,675 0,046 45,60 11,00
    16 SM C18:1 sphingomyelin with acyl residue sum C18:1 -0,803 0,009 64,55 10,32
    17 alpha-KGA alpha-Ketoglutaric acid -0,730 0,025 53,34 9,94
    18 Trp Tryptophane 0,562 0,115 31,62 9,66
    19 SM (OH) C24:1 Hydroxysphingomyelin with acyl residue sum C24:1 -0,707 0,033 50,03 9,00
    20 SM (OH) C 16:1 Hydroxysphingomyelin with acyl residue sum C 16:1 -0,778 0,014 60,46 8,95
    21 Cholestenone Cholestenone -0,644 0,061 41,48 8,92
    22 C5:1-DC Glutaconylcarnitine/Mesaconylcarnitine (Undecanoylcarnitine) 0,578 0,103 33,40 8,59
    23 Lys Lysine 0,662 0,052 43,88 8,49
    24 Histamine Histamine -0,547 0,127 29,94 7,45
    25 His Histidine 0,756 0,018 57,13 7,28
    26 Lac Lactate 0,670 0,048 44,84 7,22
    27 Phe Phenylalanine 0,681 0,044 46,35 6,16
    28 C6:1 Hexenoylcarnitine 0,546 0,128 29,85 5,70
    29 SM C18:0 sphingomyelin with acyl residue sum C18:0 -0,689 0,040 47,53 5,20
    30 20a-OH-C 20a-Hydroxycholesterol 0,550 0,125 30,28 5,12
    31 24-DH-Lanosterol 24-Dihydrolanosterol -0,655 0,055 42,92 4,18
    32 Kynurenine Kynurenine 0,445 0,230 19,79 4,13
    33 Leu Leucine 0,666 0,050 44,31 4,08
    34 SM C20:2 sphingomyelin with acyl residue sum C20:2 -0,490 0,181 23,98 4,08
    35 Ala Alanine 0,641 0,063 41,15 3,98
    36 C 14:1 Tetradecenoylcarnitine [Myristoleylcarnitine] -0,523 0,148 27,40 3,68
    37 LTB4 Leukotriene B4 0,389 0,301 15,12 3,40
    38 Suc Succinic acid 0,368 0,330 13,53 3,32
    39 TXB2 Tromboxane B2 0,313 0,412 9,80 2,79
    40 Fum Fumaric acid 0,443 0,232 19,62 2,74
    41 Gly Glycine 0,461 0,211 21,30 2,15
    42 25-OH-C 25-Hydroxycholesterol -0,343 0,366 11,78 2,03
    43 SM C26:1 sphingomyelin with acyl residue sum C26:1 -0,589 0,095 34,74 1,85
    44 Ser Serine 0,413 0,269 17,04 1,52
    45 alpha-AAA 2-Aminoadipic acid 0,394 0,294 15,52 1,39
    46 8-iso-PGF2a 8-iso-Prostaglandin F2alpha 0,443 0,232 19,66 1,37
    47 Val Valine 0,508 0,163 25,76 1,19
    48 Asn Asparagine 0,546 0,128 29,79 1,14
    49 Pent-P Pentosephosphate (e.g. Ribose-5-phosphate + Ribulose-5-phosphate) 0,514 0,157 26,44 1,14
    50 total DMA Total dimethylarginine 0,546 0,128 29,80 1,12
    51 Creatinine Creatinine -0,199 0,607 3,97 1,04
  • In the attached Figure 2a, the distribution of accuracies that can be achieved in models formed with a lead metabolite is illustrated.
  • Figure 2a illustrates the predictive abilities of combinations of metabolites based on a lead metabolite correlating with the extent of brain damage in the basal ganglia. The box-and-whisker diagrams represent the distribution of the cross-validated correlation coefficient (y-axis) for combinations comprising a lead metabolite (x-axis) and up to 7 metabolites from the initial dataset.
  • In the attached Figure 2b, the distribution of the accuracies that can be achieved in models comprising up to 7 metabolites is illustrated.
  • Figure 2b illustrates the predictive abilities (i.e. accuracy) of all adequate metabolite combinations correlating with the extent of brain damage in the basal ganglia. The box-and-whisker diagrams represent the distribution of the cross-validated correlation coefficient (y-axis) for combinations of 2 to 7 (x-axis) metabolites.
  • In the attached Figure 2c the probability of a metabolite to enter a model with adequate accuracy is illustrated.
  • Figure 2c illustrates the probabilities of single metabolites to enter a combination of metabolites correlating with the extent of brain damage in the basal ganglia. Probabilities are calculated over all models presented in Figure 2b. Metabolites are sorted according to their likelihood to be included in a model and graphed back-to-back depending of their respective (i.e. positive or negative) contributions to the regression models. Left: metabolites inducing less damage in the basal ganglia. Right: metabolites inducing more damage in the basal ganglia.
  • Example 3: Hypoxia -induced effect on neurological score
  • Lack oxygen resulted in alteration of the neurobehavioural score at 4 hourly time points in the first 24hours and at 48h. This score contains 9 items of maximal 2 points, so the maximal score is 18 points and exists of the nine neurologic items as described above. Blood samples were taken 30 minutes after the period of lack of oxygen and the metabolite concentrations were analysed as described above. These metabolite concentrations were then correlated with the neurobehavioural score. Table 7 summarizes the result of univariate correlation statistics between metabolite concentration as determined in plasma 30 minutes after asphyxia and the neurological behavioural score at 48 hours after asphyxia. For each metabolite, Pearson correlation coefficient (Cor) and its corresponding p value are given alongside the coefficient of determination (Rsq). Prob designates the actual probability (in %) to enter a combination of metabolites. Table 7: Outcome parameter: Brain Injury indicated by neurological behavioural score
    Short Full name Cor Pvalue Rsq Prob
    1 27-OH-C 27-Hydroxycholesterol 0,072 0,853 0,53 41,14
    2 Fum Fumaric acid 0,443 0,232 19,62 36,54
    3 Carnosine Carnosine -0,286 0,456 8,17 30,13
    4 total DMA Total dimethylarginine 0,546 0,128 29,80 23,57
    5 C5-DC (C6-OH) Glutarylcarnitine 0,188 0,628 3,53 19,11
    6 SDMA Symmetric dimethylarginine 0,424 0,256 17,94 18,27
    7 C5:1 Tiglylcarnitine / 3-Methyl-crotonylcarnitine -0,051 0,896 0,26 17,99
    8 Met-SO Methionine-Sulfoxide 0,774 0,014 59,97 17,15
    9 C 10:2 Decadienoylcarnitine -0,303 0,428 9,17 15,76
    10 SM (OH) C22:2 Hydroxysphingomyelin with acyl residue sum C22:2 -0,840 0,005 70,54 15,06
    11 C8:1 Octenoylcarnitine -0,272 0,479 7,40 12,83
    12 Phe Phenylalanine 0,681 0,044 46,35 9,76
    13 Ac-Orn N-acetylornithine 0,699 0,036 48,86 9,07
    14 SM (OH) C 14:1 Hydroxysphingomyelin with acyl residue sum C14:1 -0,770 0,015 59,36 9,07
    15 24,25-EpoxyC 24,25-Epoxycholesterol 0,063 0,872 0,40 8,51
    16 Tyr Tyrosine 0,803 0,009 64,48 8,09
    17 alpha-AAA 2-Aminoadipic acid 0,394 0,294 15,52 6,69
    18 C14:1 Tetradecenoylcarnitine [Myristoleylcarnitine] -0,523 0,148 27,40 6,69
    19 Pent-P Pentosephosphate (e.g. Ribose-5-phosphate + Ribulose-5-phosphate) 0,514 0,157 26,44 6,28
    20 C6 (C4:1-DC) Hexanoylcarnitine [Caproylcarnitine] -0,245 0,525 6,00 5,86
    21 SM C16:1 sphingomyelin with acyl residue sum C16:1 -0,772 0,015 59,52 4,88
    22 C14:1-OH 3-Hydroxytetradecenoylcarnitine [3-Hydroxymyristoleylcarnitine] -0,334 0,379 11,18 4,32
    23 SM C24:1 sphingomyelin with acyl residue sum C24:1 -0,805 0,009 64,75 4,04
    24 Cholestenone Cholestenone -0,644 0,061 41,48 3,77
    25 Lac Lactate 0,670 0,048 44,84 3,63
    26 8-iso-PGF2a 8-iso-Prostaglandin F2alpha 0,443 0,232 19,66 3,49
    27 3b,5a,6b-THC 3ß,5α,6ß-Trihydroxycholestan -0,114 0,769 1,31 3,49
    28 Suc Succinic acid 0,368 0,330 13,53 3,21
    29 C0 Carnitine (free) 0,068 0,862 0,46 3,07
    30 24-DH-Lanosterol 24-Dihydrolanosterol -0,655 0,055 42,92 2,65
    31 Val Valine 0,508 0,163 25,76 2,65
    32 SM C16:0 sphingomyelin with acyl residue sum C16:0 -0,713 0,031 50,91 2,65
    33 C3-DC (C4-OH) 3-Hydroxybutyrylcarnitine / Malonylcarnitine 0,173 0,657 2,98 2,65
    34 Lys Lysine 0,662 0,052 43,88 2,37
    35 Leu Leucine 0,666 0,050 44,31 2,37
    36 SM C26:0 sphingomyelin with acyl residue sum C26:0 0,184 0,635 3,40 2,37
    37 Cit Citrulline 0,032 0,935 0,10 2,23
    38 LTB4 Leukotriene B4 0,389 0,301 15,12 2,09
    39 5a,6a-EpoxyC 5α,6α-Epoxycholesterol -0,166 0,669 2,76 2,09
    40 C4:1 Butenoylcarnitine -0,078 0,841 0,61 2,09
    41 Met Methionine 0,821 0,007 67,41 1,95
    42 C5:1-DC Glutaconylcarnitine / Mesaconylcarnitine (Undecanoylcarnitine) 0,578 0,103 33,40 1,95
    43 Pro Proline 0,812 0,008 66,00 1,81
    44 SM (OH) C16:1 Hydroxysphingomyelin with acyl residue sum C16:1 -0,778 0,014 60,46 1,81
    45 C14:2-OH 3-Hydroxytetradecadienoylcarnitine 0,196 0,614 3,83 1,81
    46 Thr Threonine 0,482 0,189 23,24 1,53
    47 SM (OH) C22:1 Hydroxysphingomyelin with acyl residue sum C22:1 -0,768 0,016 59,00 1,12
  • In the attached Figure 3a, the distribution of accuracies that can be achieved in models formed with a lead metabolite is illustrated.
  • Figure 3a illustrates the predictive abilities of the combination of metabolites based on a lead metabolite correlating with the extent of brain injury as described by the neurological score at 48h. The box-and-whisker diagrams represent the distribution of the cross-validated correlation coefficient (y-axis) for combinations comprising a lead metabolite (x-axis) and up to 6 metabolites from the initial dataset.
  • In the attached Figure 3b, the distribution of the accuracies that can be achieved in models comprising up to 6 metabolites is illustrated.
  • Figure 3b illustrates the predictive abilities (i.e. accuracy) of all adequate metabolite combinations correlating with the extent of brain injury as described by the neurological score at 48h. The box-and-whisker diagrams represent the distribution of the cross-validated correlation coefficient (y-axis) for combinations of 2 to 6 (x-axis) metabolites.
  • In the attached Figure 3c the probability of a metabolite to enter a model with adequate accuracy is illustrated.
  • Figure 3c illustrates the probabilities of single metabolites to enter a combination of metabolites correlating with the extent of brain injury as described by the neurological score at 48h. Probabilities are calculated over all models presented in Figure 3b. Metabolites are sorted according to their likelihood to be included in a model and graphed back-to-back depending of their respective (i.e. positive or negative) contributions to the regression models. Left: metabolites worsening the neurological outcome. Right: metabolites improving the neurological outcome.
  • Explanation on attached Tables 8 to 13:
  • The data were generated as described above in the Material and Methods section.
  • The attached Tables 8, 9 and 10 summarise the obtained metabolite combinations. Preferred combinations are listed in Tables 11, 12 and 13.
  • In particular these tables are related to:
    • Tables 8 and 11: Combination of metabolites, correlated with affection of hippocampus brain tissue
    • Tables 9 and 12: Combination of metabolites, correlated with affection of basal ganglia brain tissue
    • Tables 10 and 13: Combination of metabolites, correlated with neurological behavioural score
  • The following parameters are shown in tables 8, 9 and 10:
  • Npar
    = total number of parameters (metabolites) in the model
    Chemical class
    = metabolite chemical classes represented in the model
    Accuracy
    = defined as the correlation coefficient (given in %) between true and predicted predictand values
    Model
    = List of metabolites in the model
  • The following parameters are shown in tables 11, 12 and 13:
  • Npar
    = total number of metabolites in the final model
    Accuracy
    = defined as the correlation coefficient (given in %) between true and predicted predictand values
    Lead metabolite
    = lead metabolite of the model
    Additional metabolites
    = list of metabolites accompanying the lead metabolite in the final model
  • The disclosure of documents cited herein is incorporated by reference Table 8: Metabolite combinations describing damage of hippocampus
    No Npar Chemical Class Accuracy Model
    1 3 En.Met/Ac.Ca./S.L. 83,2 Lac ; C5:1 ; SM C24:1
    2 3 En.Met/B.Am. 93,4 Lac ; Suc ; Carnosine
    3 2 En.Met 94,4 Lac ; Pent-P
    4 3 En.Met/B.Am. 92,4 Fum ; Lac ; Ac-Orn
    5 4 En.Met/Ac.Ca./S.L./B.Am. 83,3 Pent-P ; C16:2 ; SM C24:1 ; Carnosine
    6 4 En.Met/S.L./B.Am./O.St. 79,2 Lac ; SM (OH) C22:1 ; Carnosine ; 25-OH-C
    7 4 En.Met/Ac.Ca. 86,4 Fum ; Lac; Pent-P ; C5:1-DC
    8 2 En.Met/B.Am. 92,7 Fum ; Ac-Orn
    9 3 En.Met/Ac.Ca./B.Am. 90 Fum ; C16:2 ; Ac-Orn
    10 3 En.Met/B.Am. 91,7 Fum ; Ac-Orn ; Carnosine
    11 4 En.Met/B.Am. 79,4 Fum ; ADMA ; Carnosine ; Met-SO
    12 5 En.Met/Ac.Ca./B.Am./P.G. 79,3 Fum ; Lac ; C10:2 ; Met-SO ; 8-iso-PGF2a
    13 4 Ac.Ca./S.L./Am.Ac./B.Am. 81,9 C16:2 ; SM C24:1 ; Gln ; Met-SO
    14 3 En.Met/Am.Ac./B.Am. 90,9 Fum ; Cit ; Ac-Orn
    15 4 En.Met/Ac.Ca./B.Am. 88,7 Lac ; C10:2 ; C5:1-DC ; Carnosine
    16 3 En.Met/Ac.Ca./B.Am. 80,3 Fum ; C16:2 ; Met-SO
    17 3 En.Met/S.L./B.Am. 84,8 Lac ; SM C24:1 ; Carnosine
    18 4 En.Met 80,2 Fum ; Lac ; Pent-P ; H1
    19 4 En.Met/Ac.Ca./S.L./B.Am. 85,5 Pent-P ; C16:2 ; SM (OH) C22:2 ; Ac-Orn
    20 3 En.Met/Ac.Ca. 83,6 Fum ; C4:1 ; C5:1-DC
    21 3 En.Met/Ac.Ca./B.Am. 81,8 Fum ; C5:1-DC ; Carnosine
    22 3 En.Met/B.Am. 89,9 Fum ; Pent-P ; Ac-Orn
    23 5 En.Met/S.L./B.Am./O.St. 79,1 Fum ; SM (OH) C14:1 ; Ac-Orn ; 24-DH-Lanosterol ; 3b,5a,6b-THC
    24 5 En.Met/S.L./Am.Ac./O.St. 81,4 Lac ; SM (OH) C22:1 ; SM (OH) C22:2 ; Lys ; 25-OH-C
    25 3 En.Met/Ac.Ca./B.Am. 79,3 Lac ; C8:1 ; Carnosine
    26 3 En.Met/B.Am. I 86,5 Lac ; Ac-Orn ; Carnosine
    27 4 En.Met/Am.Ac. I 81,6 Fum ; Lac ; Suc ; Phe
    28 3 En.Met/Ac.Ca./B.Am. 94 Fum ; C5:1-DC ; Ac-Orn
    29 3 En.Met/S.L./B.Am. 80,7 Lac ; SM (OH) C22:2 ; Carnosine
    30 3 En.Met/Ac.Ca. 84,6 Lac ; C4:1 ; C5:1-DC
    31 3 En.Met/B.Am. 87 Fum ; Ac-Orn ; ADMA
    32 4 En.Met/B.Am. 86,4 Fum ; Lac ; Suc ; Met-SO
    33 4 En. Met/S. L./O. St./P.G. 81,7 Lac ; SM (OH) C22:2 ; 3b,5a,6b-THC ; 8-iso-PGF2a
    34 4 En.Met/Ac.Ca./P.G. 84 Fum ; Lac ; C5:1-DC ; 8-iso-PGF2a
    35 3 En.Met/Ac.Ca. 83,6 Fum ; C10:2 ; C5:1-DC
    36 5 En.Met/Ac.Ca./S.L./B.Am./P.G. 84 Fum ; C16:2 ; SM (OH) C22:2 ; Ac-Orn ; LTB4
    37 4 En.Met/Ac.Ca./S.L./B.Am. 86,2 Lac ; C16:2 ; SM C24:1 ; Ac-Orn
    38 3 En.Met/Ac.Ca. 82,2 Lac ; C10:2 ; C5:1-DC
    39 3 En.Met/Ac.Ca./Am.Ac. 86,6 Lac ; C10:2 ; Phe
    40 3 En.Met/Ac.Ca./B.Am. 91,5 Fum ; C10:2 ; Ac-Orn
    41 4 En.Met/S.L./B.Am. 81,3 Fum ; SM C24:1 ; SM (OH) C22:2 ; Ac-Orn
    42 5 En.Met/Am.Ac./B.Am./O.St. 83,6 Fum ; Arg ; Lys ; Ac-Orn ; 25-OH-C
    43 5 En.Met/S.L./B.Am. 86 Lac ; SM C24:0 ; SM (OH) C22:1 ; Ac-Orn ; Carnosine
    44 3 Ac.Ca./S.L./B.Am. 81,6 C16:2 ; SM C24:1 ; Carnosine
    45 4 En.Met/Ac.Ca./B.Am. 83,6 Fum ; C10:2 ; C5:1-DC ; Carnosine
    46 4 En.Met/Ac.Ca./B.Am. 89,1 Lac ; C10:2 ; Ac-Orn ; Carnosine
    47 5 En.Met/Ac.Ca./S.L./B.Am./O.St. 87,6 Lac ; C5:1 ; SM C24:1 ; Ac-Orn ; 5a,6a-EpoxyC
    48 4 En.Met/Ac.Ca./Am.Ac./O.St. 81 Lac; C5:1-DC ; Pro ; 27-OH-C
    49 4 En.Met/B.Am./O.St. 87,6 Lac; Ac-Orn ; Carnosine ; 5a,6a-EpoxyC
    50 3 En.Met/Am.Ac./B.Am. 90,6 Lac ; Cit ; Ac-Orn
    51 4 En.Met/Ac.Ca./B.Am. 85,8 Lac; C5:1 ; H1 ; Ac-Orn
    52 4 En.Met/Ac.Ca./B.Am. 88,8 Lac ; C5:1 ; Ac-Orn ; Carnosine
    53 4 En.Met/B.Am. 85,4 Lac ; Ac-Orn ; Carnosine ; Creatinine
    54 4 En.Met/Ac.Ca./Am.Ac./B.Am. 84,2 Lac ; C16:2 ; Cit; Ac-Orn
    55 4 En.Met/Ac.Ca./S.L. 84,3 Lac ; Suc ; C16:2 ; SM C24:1
    56 4 En.Met/Ac.Ca./S.L./B.Am. 92,8 Lac ; C5:1 ; SM C24:1 ; Carnosine
    57 3 En.Met/B.Am. 82,1 Fum ; Lac ; Met-SO
    58 4 En.Met/B.Am./O.St. 93,3 H1 ; Creatinine ; total DMA ; 3b,5a,6b-THC
    59 4 En.Met/Ac.Ca./S.L./B.Am. 86 Lac ; C5:1 ; SM (OH) C22:2 ; Ac-Orn
    60 4 En.Met/S.L./Am.Ac./O.St. 83,6 Lac ; SM (OH) C22:2 ; Lys ; 25-OH-C
    61 3 Ac.Ca./S.L. 85,1 C16:2 ; C5:1 ; SM C24:1
    62 4 En.Met/Ac.Ca./S.L./B.Am. 89 Lac ; C5-DC (C6-OH) ; SM C18:1 ; Carnosine
    63 4 En.Met/Ac.Ca./B.Am./P.G. 91,3 Fum ; C10:2 ; Ac-Orn ; 8-iso-PGF2a
    64 4 En.Met/B.Am. 94,8 Hex-P ; Lac ; Pent-P ; Carnosine
    65 4 En.Met/Ac.Ca./B.Am. 84,9 Lac ; C4:1 ; C5:1-DC ; Carnosine
    66 4 En.Met/S.L./O.St. 81,8 Lac ; SM C16:1 ; SM (OH) C22:2 ; 24S-OH-C
    67 4 Ac.Ca./B.Am./O.St. 82,2 C10:2 ; C5:1-DC ; alpha-AAA ; 3b,5a,6b-THC
    68 4 En.Met/Ac.Ca./B.Am./O.St. 79,3 Lac ; C5:1-DC ; Ac-Orn ; 27-OH-C
    69 4 En.Met/Ac.Ca./B.Am. 86,7 Suc ; C5:1-DC ; alpha-AAA ; Carnosine
    70 5 En.Met/Am.Ac./B.Am./O.St. 85,3 Fum ; Orn ; Pro ; Ac-Orn ; 24S-OH-C
    71 5 En.Met/Ac.Ca./Am.Ac./B.Am. 79,8 Lac ; C10:2 ; Arg Or ; Ac-Orn
    72 3 En.Met/B.Am./O.St. 81,2 Lac ; total DMA ; 3b,5a,6b-THC
    73 3 En.Met/B.Am./O.St. 83,1 Lac ; Ac-Orn ; 5a,6a-EpoxyC
    74 4 En.Met/Ac.Ca. 84,4 Lac; Pent-P ; C4:1 ; C5:1-DC
    75 4 En.Met/Ac.Ca./B.Am. 80 Hex-P ; Lac; C8:1 ; Ac-Orn
    76 4 En.Met/Ac.Ca./B.Am. 92,7 Fum ; C16:2 ; Ac-Orn ; Met-SO
    77 4 En.Met/Ac.Ca./S.L./O.St. 83,7 Lac ; C6:1 ; SM C16:1 ; 25-OH-C
    78 4 En.Met/B.Am. 80,7 Fum ; Carnosine ; Creatinine ; Met-SO
    79 3 Ac.Ca./S.L./B.Am. 83,3 C16:2 ; SM C24:1 ; Ac-Orn
    80 4 En.Met/Ac.Ca./S.L. 82,9 Fum ; Lac ; C5:1-DC ; SM (OH) C22:2
    81 4 En.Met/Ac.Ca./S.L./B.Am. 85,8 Pent-P ; C16:2 ; SM C24:1 ; Ac-Orn
    82 5 En.Met/Am.Ac./B.Am./O.St. 85 Lac ; Arg ; Carnosine ; Met-SO ; 27-OH-C
    83 4 En.Met/B.Am./O.St. 82,4 Lac ; Ac-Orn ; ADMA ; 27-OH-C
    84 4 En.Met/B.Am. 91,1 Fum ; Lac ; Ac-Orn ; Carnosine
    85 4 En.Met/Am.Ac./P.G. 79,8 Fum ; Lac ; Phe ; 8-iso-PGF2a
    86 4 En.Met/Ac.Ca./S.L./B.Am. 87 Fum ; C5:1-DC ; SM (OH) C22:2 ; Carnosine
    87 5 Ac.Ca./S.L./B.Am. 81 C10:2 ; C16:2 ; SM (OH) C22:2 ; Ac-Orn ; Carnosine
    88 4 En.Met/B.Am. 87,9 Fum; Lac; Ac-Orn ; ADMA
    89 5 En.Met/B.Am. 79,9 Fum ; Lac ; ADMA ; Carnosine ; Met-SO
    90 4 En.Met/Ac.Ca./B.Am. 81,5 Fum ; Pent-P ; C16:2 ; Met-SO
    91 5 Ac.Ca./S.L./B.Am. 81,1 C16:2 ; SM C24:1 ; SM C26:1 ; SM (OH) C22:1 ; Ac-Orn
    92 4 En.Met/Am.Ac./B.Am./O.St. 82,9 Lac ; Phe ; Ac-Orn ; 27-OH-C
    93 5 En.Met/B.Am. 82,3 Lac ; Pent-P ; ADMA ; SDMA ; total DMA
    94 5 En.Met/B.Am./O.St. 80,2 Lac; Suc ; ADMA; total DMA; 3b,5a,6b-THC
    95 3 En.Met/B.Am. 81,3 Lac ; Creatinine ; total DMA
    96 6 En.Met/Ac.Ca./S.L./B.Am./O.St. 88,2 Lac ; C16:2 ; SM (OH) C22:2 ; Ac-Orn ; ADMA ; 27-OH-C
    97 4 En.Met/Ac.Ca./S.L./O.St. 79,9 Lac ; C10:2 ; SM (OH) C22:2 ; 3b,5a,6b-THC
    98 4 En.Met/Am.Ac./O.St./P.G. 79 Lac ; Orn ; 3b,5a,6b-THC ; 8-iso-PGF2a
    99 4 En.Met/Am.Ac./B.Am./P.G. 79,8 Fum ; Met; Ac-Orn ; DHA
    100 5 En.Met/B.Am./O.St. 82,2 Lac ; H1 ; ADMA ; Met-SO ; 27-OH-C
    101 4 En.Met/B.Am. 95 Lac ; Pent-P ; Suc ; Carnosine
    102 4 En.Met/B.Am./O.St. 87,6 Fum ; Ac-Orn ; ADMA ; 3b,5a,6b-THC
    103 4 En.Met/Ac.Ca. 83,9 Fum ; Lac; C5:1-DC; C8:1
    104 4 Ac.Ca./S.L./B.Am. 81 C16; C5:1-DC ; SM (OH) C14:1 ; Carnosine
    105 4 En.Met/S.L./O.St. 80 Lac ; SM (OH) C22:1 ; 24S-OH-C ; 25-OH-C
    106 5 En.Met/Ac.Ca./S.L./B.Am. 84,8 Fum ; C5:1-DC ; SM C16:1 ; SM (OH) C14:1 ; Carnosine
    107 4 En.Met/S.L./B.Am. 81,9 Fum ; SM C16:0 ; SM (OH) C22:2 ; Ac-Orn
    108 4 En.Met/Ac.Ca./B.Am. 79,5 Fum; Lac; C5:1 ; Met-SO
    109 4 En.Met/Ac.Ca./B.Am. 81,5 Lac ; C16:2 ; Ac-Orn ; Carnosine
    110 4 En.Met/B.Am. 93,8 Fum ; Lac ; Pent-P ; Ac-Orn
    111 4 En.Met/Ac.Ca./S.L./B.Am. 81,6 Lac ; C5:1 ; SM C24:1 ; Ac-Orn
    112 4 En.Met/Ac.Ca. 80,7 Fum ; Lac ; C10:2 ; C5:1-DC
    113 6 En.Met/Ac.Ca./B.Am./P.G. 84,8 Fum ; Pent-P ; C18:2 ; Ac-Orn ; Met-SO ; LTB4
    114 4 En.Met/B.Am./O.St./P.G. 85,7 Lac ; total DMA ; 3b,5a,6b-THC ; 8-iso-PGF2a
    115 4 En.Met/Ac.Ca./B.Am. 84,6 Fum ; Lac ; C5:1-DC ; SDMA
    116 4 En.Met/Ac.Ca./B.Am. 82,7 Fum ; C4:1 ; C5:1-DC ; Carnosine
    117 4 En.Met/Ac.Ca./B.Am. 89,7 Lac; Pent-P ; C10:2 ; Ac-Orn
    118 4 En.Met/Am.Ac./P.G. 81,8 Lac ; Suc ; Orn ; 8-iso-PGF2a
    119 4 Ac.Ca./S.L./B.Am. 82,7 C5:1 ; SM C24:1 ; ADMA ; Carnosine
    120 4 En.Met/Ac.Ca. 82,7 Fum ; Pent-P ; Suc ; C5:1-DC
    121 4 En.Met/Ac.Ca./B.Am. 89,4 Fum ; C10:2 ; C16:2 ; Ac-Orn
    122 4 En.Met/B.Am. 80,2 Fum ; Lac ; Pent-P ; ADMA
    123 4 En.Met/Ac.Ca./B.Am. 80 Lac ; C10:2 ; Carnosine ; Met-SO
    124 4 En.Met/B.Am./O.St. 83,2 Fum ; ADMA ; Met-SO ; 27-OH-C
    125 4 En.Met/Ac.Ca./B.Am./O.St. 79,9 Lac ; C5:1 ; Ac-Orn ; 3b,5a,6b-THC
    126 4 En.Met/Am.Ac./B.Am./P.G. 80 Lac ; Phe ; Carnosine ; LTB4
    127 5 En.Met/Ac.Ca./S.L./B.Am./O.St. 86,7 Lac ; C8:1 ; SM C18:1 ; ADMA ; 27-OH-C
    128 4 Ac.Ca./S.L./B.Am. 88,1 C16:2 ; C5:1 ; SM C24:1 ; Ac-Orn
    129 4 En.Met/B.Am. 83,3 Fum ; Lac ; Suc ; Carnosine
    130 4 En.Met/Ac.Ca./B.Am. 87,2 Fum ; Lac ; C5:1-DC ; total DMA
    131 4 En.Met/Ac.Ca./S.L./B.Am. 80,7 Lac ; C5:1 ; SM (OH) C16:1 ; Carnosine
    132 5 En.Met/B.Am./O.St. 90,3 Fum ; Ac-Orn ; total DMA ; Cholestenone ; 3b,5a,6b-THC
    133 6 En.Met/Ac.Ca./Am.Ac./B.Am. 85,9 Fum ; C16:2 ; Met; Ac-Orn ; Histamine ; Met-SO
    134 4 En.Met/Ac.Ca. 81,6 Fum ; Lac; Pent-P ; C10:2
    135 4 En.Met/Ac.Ca./B.Am. 89,5 Fum ; C5:1-DC ; Creatinine ; total DMA
    136 4 Ac.Ca./S.L./B.Am. 82,2 C16:2 ; C5:1 ; SM (OH) C22:2 ; Ac-Orn
    137 5 En.Met/Am.Ac./B.Am./O.St. 84,4 Lac ; Pent-P ; Pro ; ADMA ; 27-OH-C
    138 4 En.Met/Ac.Ca./S.L. 81 Fum ; C5:1-DC ; SM (OH) C14:1 ; SM (OH) C22:2
    139 4 En.Met/S.L./B.Am. 80,8 Fum ; SM C26:1 ; SM (OH) C22:1 ; Ac-Orn
    140 4 En.Met/Ac.Ca./B.Am./P.G. 79,8 Lac ; C10:2 ; Ac-Orn ; LTB4
    141 4 En.Met/Ac.Ca./Am.Ac./B.Am. 91 Fum; C16:2 ; Cit ; Ac-Orn
    142 4 En.Met/S.L./Am.Ac./O.St. 81,8 Lac ; SM (OH) C22:2 ; Gln ; 25-OH-C
    143 4 En.Met/P.G. 83,5 Fum ; Lac ; Pent-P ; 8-iso-PGF2a
    144 4 Ac.Ca./B.Am./O.St. 91,7 C5:1-DC ; alpha-AAA ; 24S-OH-C ; 25-OH-C
    145 4 En.Met/B.Am. 80,3 Fum ; Lac ; Carnosine ; Met-SO
    Figure imgb0001
    Figure imgb0002
    Figure imgb0003
    Figure imgb0004
    Figure imgb0005
    Figure imgb0006
    Figure imgb0007
    Figure imgb0008
    Figure imgb0009
    Figure imgb0010
    Figure imgb0011
    Figure imgb0012
    Figure imgb0013
    Figure imgb0014
    Figure imgb0015
    Figure imgb0016
    Figure imgb0017
    Figure imgb0018
    Figure imgb0019
    Figure imgb0020
    Figure imgb0021
    Figure imgb0022
    Figure imgb0023
    Figure imgb0024
    Figure imgb0025
    Figure imgb0026
    Figure imgb0027
    Figure imgb0028
    Figure imgb0029
    Figure imgb0030
    Figure imgb0031
    Figure imgb0032
    Figure imgb0033
    Figure imgb0034
    Figure imgb0035
    Figure imgb0036
    Figure imgb0037
    Figure imgb0038
    Figure imgb0039
    Figure imgb0040
    Figure imgb0041
    Figure imgb0042
    Figure imgb0043
    Figure imgb0044
    Figure imgb0045
    Figure imgb0046
    Figure imgb0047
    Figure imgb0048
    Figure imgb0049
    Figure imgb0050
    Figure imgb0051
    Figure imgb0052
    Figure imgb0053
    Figure imgb0054
    Figure imgb0055
    Figure imgb0056
    Figure imgb0057
    Figure imgb0058
    Figure imgb0059
    Figure imgb0060
    Figure imgb0061
    Figure imgb0062
    Figure imgb0063
    Figure imgb0064
    Figure imgb0065
    Figure imgb0066
    Figure imgb0067
    Figure imgb0068
    Figure imgb0069
    Figure imgb0070
    Figure imgb0071
    Figure imgb0072
    Figure imgb0073
    Figure imgb0074
    Figure imgb0075
    Figure imgb0076
    Figure imgb0077
    Figure imgb0078
    Figure imgb0079
    Figure imgb0080
    Figure imgb0081
    Figure imgb0082
    Figure imgb0083
    Figure imgb0084
    Figure imgb0085
    Figure imgb0086
    Figure imgb0087
    Figure imgb0088
    Figure imgb0089
    Figure imgb0090
    Figure imgb0091
    Figure imgb0092
    Figure imgb0093
    Figure imgb0094
    Figure imgb0095
    Figure imgb0096
    Figure imgb0097
    Figure imgb0098
    Figure imgb0099
    Figure imgb0100
    Figure imgb0101
    Figure imgb0102
    Figure imgb0103
    Figure imgb0104
    Figure imgb0105
    Figure imgb0106
    Figure imgb0107
    Figure imgb0108
    Figure imgb0109
    Figure imgb0110
    Figure imgb0111
    Figure imgb0112
    Figure imgb0113
    Figure imgb0114
    Figure imgb0115
    Figure imgb0116
    Figure imgb0117
    Figure imgb0118
    Figure imgb0119
    Figure imgb0120
    Figure imgb0121
    Figure imgb0122
    Figure imgb0123
    Figure imgb0124
    Figure imgb0125
    Figure imgb0126
    Figure imgb0127
    Figure imgb0128
    Table 10: Metabolite combinations correlating with neurological behavioural score
    No. Npar Chemical Class Accuracy Model
    1 2 Am.Ac./O.St. 92,2 Tyr ; 27-OH-C
    2 2 En.Met/B.Am. 83,3 Fum ; total DMA
    3 4 En.Met/B.Am./O.St. 95,3 Fum ; Met-SO ; 24-DH-Lanosterol ; 27-OH-C
    4 3 En.Met/Ac.Ca./B.Am. 79,8 Fum ; C8:1 ; SDMA
    5 4 En.Met/Ac.Ca./O.St. 81,1 Pent-P ; C10:2 ; C14:2-OH ; 27-OH-C
    6 3 Ac.Ca./S.L./B.Am. 79,5 C5:1 ; SM (OH) C14:1 ; SDMA
    7 2 Ac.Ca./B.Am. 79,5 C14:1-OH ; Carnosine
    8 5 Ac.Ca./Am.Ac./B.Am. 88,9 C5-DC (C6-OH) ; Pro ; Creatinine ; SDMA ; total DMA
    9 3 En.Met/Ac.Ca./B.Am. 91,4 Fum ; C5:1 ; total DMA
    10 4 S.L./Am.Ac./O.St. 84,7 SM (OH) C16:1 ; SM (OH) C22:1 ; Phe ; 27-OH-C
    11 3 B.Am./O.St. 89 Met-SO ; 24,25-EpoxyC ; 27-OH-C
    12 3 Ac.Ca./B.Am. 83,3 C14:1-OH ; C6 (C4:1-DC); Carnosine
    13 3 Ac.Ca./B.Am./O.St. 90,1 C5:1 ; total DMA ; 27-OH-C
    14 2 Ac.Ca./B.Am. 85,8 C6 (C4:1-DC) ; Carnosine
    15 3 Ac.Ca./B.Am. 79,6 C5-DC (C6-OH) ; alpha-AAA ; total DMA
    16 3 Am.Ac./B.Am./O.St. 96,1 Tyr; total DMA; 27-OH-C
    17 4 Ac.Ca./Am.Ac./B.Am./O.St. 84 C8:1 ; Leu ; SDMA ; 27-OH-C
    18 3 Am.Ac./B.Am./O.St. 88,7 Phe ; SDMA ; 27-OH-C
    19 3 S.L./B.Am./O.St. 88,1 SM (OH) C22:2 ; Met-SO ; 27-OH-C
    20 2 B.Am./O.St. 85,1 total DMA; 27-OH-C
    21 4 Ac.Ca./S.L./Am.Ac./B.Am. 87,8 C5-DC (C6-OH) ; SM (OH) C16:1 ; Pro ; total DMA
    22 3 Ac.Ca./B.Am. 83,7 C14:1 ; C5:1 ; total DMA
    23 4 En.Met/Ac.Ca./B.Am. 89,6 Fum ; C14:1-OH ; Carnosine ; total DMA
    24 4 En.Met/B.Am. 90,4 Fum ; Suc ; Carnosine ; SDMA
    25 3 En.Met/Am.Ac./B.Am. 79,7 Fum ; Phe ; SDMA
    26 3 Ac.Ca./S.L./B.Am. 90,1 C5:1 ; SM (OH) C22:2 ; total DMA
    27 4 En.Met/Ac.Ca./B.Am./O.St. 83,8 Suc ; C14:1 ; Carnosine; 27-OH-C
    28 3 S.L./B.Am./O.St. 88,6 SM C16:1 ; Carnosine ; 27-OH-C
    29 5 En.Met/Ac.Ca./S.L./Am.Ac./O.St. 89 Fum ; C10 ; SM (OH) C22:2 ; Phe ; 27-OH-C
    30. 4 En.Met/Ac.Ca./B.Am./O.St. 80,9 Pent-P ; C5:1 ; Met-SO ; 24,25-EpoxyC
    31 4 Ac.Ca./B.Am./O.St. 85,4 C14:1 ; Ac-Orn ; Carnosine ; 27-OH-C
    32 3 En.Met/Ac.Ca./Am.Ac. 82,4 Fum ; C8:1 ; Phe
    33 4 En.Met/O.St. 80,9 Fum ; 24-DH-Lanosterol ; 27-OH-C ; 3b,5a,6b-THC
    34 3 En.Met/Ac.Ca./Am.Ac. 84,6 Fum ; C5-DC (C6-OH) ; Met
    35 4 Ac.Ca./Am.Ac./O.St. 84,6 C5:1-DC ; Phe ; 24,25-EpoxyC ; 27-OH-C
    36 3 En.Met/Ac.Ca./B.Am. 86,8 Lac ; C14:1-OH ; Carnosine
    37 2 B.Am./O.St. 81,5 Met-SO; 27-OH-C
    38 2 En.Met/B.Am. 79,1 Fum ; SDMA
    39 3 Ac.Ca./B.Am./O.St. 84,3 C10:2 ; Met-SO ; 27-OH-C
    40 3 Ac.Ca./Am.Ac./O.St. 95,9 C10:2; Phe ; 27-OH-C
    41 3 Am.Ac./B.Am./O.St. 94,6 Phe ; total DMA ; 27-OH-C
    42 3 S.L./B.Am./O.St. 88,3 SM (OH) C14:1 ; Met-SO ; 27-OH-C
    43 6 Ac.Ca./S.L./B.Am./O.St. 86,5 C10:2 ; C5:1 ; SM C16:1 ; Met-SO ; total DMA ; 24,25-EpoxyC
    44 3 Ac.Ca./S.L./B.Am. 88,5 C5:1 ; SM (OH) C22:2 ; SDMA
    45 2 Am.Ac./O.St. 81,1 Phe ; 27-OH-C
    46 3 S.L./Am.Ac./O.St. 90,6 SM (OH) C22:2 ; Phe ; 27-OH-C
    47 3 En.Met/Ac.Ca./B.Am. 86,5 Fum ; C8:1 ; total DMA
    48 3 En.Met/Ac.Ca./B.Am. 88,3 Fum ; C14:1-OH ; Carnosine
    49 3 S.L./B.Am./O.St. 87,3 SM C16:0 ; Carnosine ; 27-OH-C
    50 3 B.Am./O.St./P.G. 88,8 Carnosine ; 27-OH-C ; DHA
    51 3 Ac.Ca./B.Am. 88 C10:2 ; C14:1 ; Carnosine
    52 4 Ac.Ca./S.L./B.Am./O.St. 83,6 C0 ; SM (OH) C22:2 ; total DMA ; 5a,6a-EpoxyC
    53 4 En.Met/Ac.Ca./B.Am. 84,4 Lac; C5 ; C8:1 ; Carnosine
    54 3 B.Am./O.St. 89,5 Met-SO ; total DMA ; 27-OH-C
    55 4 Ac.Ca./S.L./B.Am./O.St. 87 C5:1 ; SM (OH) C16:1 ; SDMA ; 27-OH-C
    56 3 En.Met/Ac.Ca./P.G. 80,6 Fum ; C14:1 ; 8-iso-PGF2a
    57 4 En.Met/B.Am./O.St. 82,3 Fum ; Suc ; Met-SO ; 24,25-EpoxyC
    58 4 En.Met/Ac.Ca./B.Am. 83,2 Fum ; C12 ; C8:1 ; Carnosine
    59 4 Ac.Ca./S.L./B.Am./O.St. 90,6 C5:1 ; SM (OH) C22:2 ; SDMA ; 3b,5a,6b-THC
    60 3 En.Met/Ac.Ca./B.Am. 87,5 Fum ; C0 ; total DMA
    61 3 B.Am./O.St. 79,8 Ac-Orn ; 24,25-EpoxyC ; 27-OH-C
    62 5 B.Am./O.St. 88,7 Ac-Orn ; Carnosine ; SDMA ; total DMA ; 27-OH-C
    63 4 S.L./B.Am./O.St. 80,5 SM (OH) C14:1 ; SDMA ; 27-OH-C ; 3b,5a,6b-THC
    64 3 B.Am./O.St. 90,2 alpha-AAA ; Met-SO ; 27-OH-C
    65 4 En.Met/Ac.Ca./B.Am. 87,8 Fum ; C12 ; Ac-Orn ; Carnosine
    66 3 Ac.Ca./S.L./B.Am. 81,1 C6 (C4:1-DC) ; SM (OH) C22:2 ; Carnosine
    67 4 Ac.Ca./B.Am./O.St. 80,6 C4:1 ; C5:1 ; Ac-Orn ; 24,25-EpoxyC
    68 3 Am.Ac./B.Am./O.St. 87,7 Cit ; Met-SO ; 27-OH-C
    69 3 Am.Ac./B.Am./O.St. 85 Met; Carnosine ; 27-OH-C
    70 4 S.L./B.Am./O.St. 87,1 SM (OH) C16:1 ; total DMA ; 27-OH-C ; Cholestenone
    71 3 Ac.Ca./B.Am. 84,4 C10:2 ; C6 (C4:1-DC) ; Carnosine
    72 3 En.Met/Ac.Ca./B.Am. 85,5 Fum ; C14:1 ; Ac-Orn
    73 5 En.Met/Ac.Ca./S.L./B.Am. 89,2 Fum ; OAA ; C5-DC (C6-OH) ; SM (OH) C22:2 ; SDMA
    74 3 En.Met/Ac.Ca./B.Am. 81,5 Fum ; C6 (C4:1-DC) ; Carnosine
    75 3 En.Met/Ac.Ca./B.Am. 80,3 Fum ; C10:2 ; Ac-Orn
    76 4 En.Met/Ac.Ca./B.Am./P.G. 88,5 Fum ; C14:1 ; Carnosine ; 8-iso-PGF2a
    77 5 En.Met/Ac.Ca./B.Am./O.St. 82 Fum ; C5 ; Ac-Orn ; Met-SO ; Cholestenone
    78 4 Ac.Ca./B.Am./P.G. 85,1 C10:2 ; C8:1 ; Carnosine ; LTB4
    79 3 Ac.Ca./B.Am./O.St. 80,5 C14:1 ; Carnosine ; 27-OH-C
    80 4 Ac.Ca./Am.Ac./B.Am./O.St. 88,2 C8:1 ; Pro ; Carnosine ; 27-OH-C
    81 4 En.Met/Am.Ac./O.St. 93,3 Fum ; Lac ; Tyr; 27-OH-C
    82 4 En.Met/Ac.Ca./Am.Ac. 90,5 Fum ; C10:2; C8:1 ; Phe
    83 4 En.Met/Ac.Ca./B.Am. 82,3 Fum ; C4:1 ; C5:1 ; Met-SO
    84 3 S.L./B.Am./O.St. 90 SM C26:0 ; Met-SO ; 27-OH-C
    85 4 S.L./B.Am./O.St. 90,8 SM (OH) C22:2 ; Carnosine ; SDMA ; 27-OH-C
    86 3 Ac.Ca./Am.Ac. 82,2 C10:2 ; C6 (C4:1-DC) ; Phe
    87 3 En.Met/Ac.Ca./B.Am. 87,7 Fum ; C14:1-OH ; total DMA
    88 4 Ac.Ca./B.Am./O.St. 90,5 C4:1 ; Met-SO ; 24,25-EpoxyC ; 27-OH-C
    89 2 Ac.Ca./B.Am. 80,6 C5:1 ; total DMA
    90 3 En.Met/B.Am. 81,9 Fum ; Met-SO ; SDMA
    91 3 B.Am./O.St. 89,9 Carnosine ; total DMA ; 27-OH-C
    92 3 En.Met/B.Am. 84,3 Fum ; Pent-P ; SDMA
    93 3 Ac.Ca./S.L./B.Am. 79,5 C6 (C4:1-DC) ; SM (OH) C14:1 ; Carnosine
    94 3 En.Met/Ac.Ca./Am.Ac. 80,3 Fum ; C10:2 ; Phe
    95 4 Ac.Ca./S.L./B.Am. 88,7 C5:1 ; SM C24:1 ; SM (OH) C22:2; SDMA
    96 3 Ac.Ca./B.Am. 83,3 C5:1 ; C8:1 ; total DMA
    97 3 En.Met/B.Am./O.St. 92,2 Fum ; total DMA ; 27-OH-C
    98 4 Ac.Ca./B.Am./O.St. 82,9 C10:2 ; C8:1 ; Met-SO ; 5a,6a-EpoxyC
    99 3 Ac.Ca./S.L./B.Am. 86,4 C5-DC (C6-OH) ; SM (OH) C22:2 ; Carnosine
    100 4 En.Met/Ac.Ca./B.Am. 86,4 Fum ; C10:2 ; C8:1 ; Met-SO
    101 3 En.Met/Ac.Ca./B.Am. 95,2 Fum ; C5-DC (C6-OH) ; total DMA
    102 3 Ac.Ca./Am.Ac./B.Am. 86,3 C5-DC (C6-OH) ; Tyr ; total DMA
    103 5 En.Met/Ac.Ca./S.L./B.Am. 82,6 Pent-P ; C3-DC (C4-OH) ; SM C24:1 ; alpha-AAA ; Carnosine
    104 4 Ac.Ca./S.L./O.St. 79,8 C5:1 ; C8:1 ; SM (OH) C14:1 ; Cholestenone
    105 4 En.Met/Ac.Ca./B.Am. 80,2 Fum ; C10:2 ; C5:1-DC ; SDMA
    106 4 Ac.Ca./S.L./B.Am. 82,9 C5:1 ; SM C24:1 ; SM (OH) C14:1 ; SDMA
    107 4 Ac.Ca./S.L./B.Am. 86,8 C5-DC (C6-OH) ; SM (OH) C14:1 ; alpha-AAA ; Carnosine
    108 3 Ac.Ca./Am.Ac. 79,1 C10:2 ; C5-DC (C6-OH) ; Phe
    109 4 En.Met/Ac.Ca./B.Am. 82,1 Lac ; C0 ; Carnosine ; total DMA
    110 3 Ac.Ca./B.Am. 81,9 C5:1 ; SDMA ; total DMA
    111 3 En.Met/Ac.Ca. 82,9 Fum ; Lac ; C14:1-OH
    112 4 En.Met/Ac.Ca./S.L./O.St. 81,9 Fum ; C14:2-OH ; SM (OH) C22:2 ; 27-OH-C
    113 3 Ac.Ca./B.Am./O.St. 79,1 C14:1-OH ; Carnosine ; 27-OH-C
    114 3 En.Met/B.Am. 87,5 Fum ; Suc ; SDMA
    115 4 En.Met/Ac.Ca./S.L./B.Am. 88 Fum ; C5-OH (C3-DC-M) ; SM (OH) C22:2 ; total DMA
    116 4 Ac.Ca./Am.Ac./O.St. 81,8 C10:2 ; C6 (C4:1-DC) ; Phe ; 24,25-EpoxyC
    117 3 En.Met/B.Am. 86 Fum ; Pent-P ; total DMA
    118 4 En.Met/Ac.Ca./B.Am./O.St. 90,1 Pent-P ; C5:1 ; total DMA ; 24,25-EpoxyC
    119 4 Am.Ac./B.Am./O.St. 91,6 Cit ; Met-SO ; SDMA ; 27-OH-C
    120 3 En.Met/Ac.Ca./B.Am. 85,8 Fum ; C14:1 ; Met-SO
    121 4 En.Met/Ac.Ca./B.Am. 90,4 Fum ; C5:1 ; Met-SO ; SDMA
    122 4 S.L./B.Am./O.St. 88,7 SM C16:1 ; Met-SO ; 27-OH-C ; Cholestenone
    123 5 S.L./B.Am./O.St./P.G. 87,8 SM (OH) C22:2 ; Met-SO ; 24-DH-Lanosterol ; 27-OH-C ; DHA
    124 3 En.Met/Am.Ac./O.St. 89,4 Fum ; Met; 27-OH-C
    125 3 En.Met/Ac.Ca./B.Am. 80,3 Fum ; C0 ; Met-SO
    126 3 En.Met/Ac.Ca./B.Am. 82,6 Fum ; C14:1-OH ; Met-SO
    127 3 En.Met/Ac.Ca./B.Am. 95,7 Lac ; C6 (C4:1-DC); Carnosine
    128 4 En.Met/Ac.Ca./B.Am. 88 Fum ; C10:2 ; C6 (C4:1-DC) ; Met-SO
    129 3 S.L./B.Am./O.St. 91,2 SM (OH) C22:2 ; Carnosine ; 27-OH-C
    130 3 B.Am./O.St. 81,6 Carnosine ; SDMA ; 27-OH-C
    131 4 En.Met/Ac.Ca./S.L./B.Am. 91,1 Pent-P ; C5-DC (C6-OH) ; SM (OH) C14:1 ; Carnosine
    132 4 En.Met/Am.Ac./B.Am./O.St. 92,6 Suc ; Lys ; SDMA; 27-OH-C
    133 4 Ac.Ca./S.L./B.Am. 85,9 C5-DC (C6-OH) ; C8:1 ; SM (OH) C14:1 ; Carnosine
    134 4 En.Met/Ac.Ca./Am.Ac. 80,1 Pent-P ; C10:2 ; C8:1 ; Tyr
    135 3 Ac.Ca./Am.Ac./O.St. 94,7 C10:2 ; Tyr ; 27-OH-C
    136 3 S.L./B.Am./O.St. 91,4 SM (OH) C22:2 ; total DMA ; 27-OH-C
    137 4 En.Met/Ac.Ca./B.Am. 87,1 Fum ; C10:2 ; C14:1 ; Ac-Orn
    138 4 En.Met/B.Am./O.St. 95,3 Fum ; Met-SO ; total DMA ; 27-OH-C
    139 4 Ac.Ca./S.L./B.Am. 90,4 C5:1 ; C8:1 ; SM C16:1 ; Carnosine
    140 5 Ac.Ca./S.L./B.Am. 79,7 C10:2 ; C5:1 ; SM C24:1 ; SM (OH) C22:2 ; Carnosine
    141 4 En.Met/B.Am./O.St. 93,9 Fum ; Pent-P ; total DMA ; 27-OH-C
    142 4 En.Met/Ac.Ca./B.Am. 89,7 Lac ; C6 (C4:1-DC) ; Carnosine ; total DMA
    143 3 S.L./Am.Ac./O.St. 82,6 SM (OH) C22:2 ; Val ; 27-OH-C
    144 3 En.Met/Ac.Ca./B.Am. 90,9 Lac ; C12 ; Carnosine
    145 4 En.Met/Ac.Ca./S.L./Am.Ac. 82,3 Fum ; C3-DC (C4-OH) ; SM (OH) C22:2 ; Tyr
    146 4 Ac.Ca./B.Am. 81,7 C0; C14:2-OH ; Carnosine; total DMA
    147 5 En.Met/Ac.Ca./B.Am./O.St. 97,2 Fum ; C14:1-OH ; Met-SO ; total DMA ; 27-OH-C
    148 4 Ac.Ca./S.L./B.Am. 83,8 C3-DC (C4-OH) ; SM C24:1 ; SM (OH) C22:2 ; Carnosine
    149 4 Ac.Ca./S.L./B.Am./O.St. 81 C5-DC (C6-OH) ; SM (OH) C22:2 ; Met-SO ; 24,25-EpoxyC
    150 5 Am.Ac./B.Am./O.St. 80,9 Phe ; Thr ; Val ; alpha-AAA ; 27-OH-C
    151 3 En.Met/Ac.Ca./B.Am. 84,7 Fum ; C6 (C4:1-DC) ; Met-SO
    152 4 Ac.Ca./Am.Ac./B.Am. 85,5 C14:2-OH ; C5-DC (C6-OH) ; Tyr ; total DMA
    153 3 Ac.Ca./S.L./B.Am. 86,6 C5:1 ; SM (OH) C14:1 ; total DMA
    154 5 Ac.Ca./S.L./B.Am./O.St. 96 C5:1 ; SM (OH) C14:1 ; Met-SO ; total DMA ; 27-OH-C
    155 4 Ac.Ca./S.L./Am.Ac./B.Am. 91,4 C5-DC (C6-OH) ; SM (OH) C14:1 ; Phe ; Carnosine
    156 4 Ac.Ca./S.L. 83,5 C10:2 ; C5:1 ; C8:1 ; SM (OH) C22:2
    157 3 En.Met/Ac.Ca./B.Am. 86,3 Fum ; C6 (C4:1-DC) ; total DMA
    158 4 En.Met/Ac.Ca./O.St. 79,2 Fum ; C10:2 ; C5:1-DC ; 24,25-EpoxyC
    159 3 En.Met/Am.Ac./O.St. 93,5 Fum ; Tyr ; 27-OH-C
    160 5 Ac.Ca./S.L./B.Am. 84,9 C5-DC (C6-OH) ; SM C18:1 ; SM (OH) C16:1 ; alpha-AAA ; Met-SO
    161 4 Ac.Ca./Am.Ac./B.Am./O.St. 86,4 C8:1 ; Met; Carnosine ; 27-OH-C
    162 3 Am.Ac./B.Am./O.St. 90,4 Lys ; total DMA ; 27-OH-C
    163 4 Ac.Ca./S.L./B.Am. 81 C10:2 ; C14:1-OH ; SM (OH) C14:1 ; Carnosine
    164 4 Ac.Ca./S.L./B.Am./O.St. 91,9 C5:1 ; SM (OH) C22:2 ; SDMA ; 27-OH-C
    165 4 En.Met/Am.Ac./B.Am./O.St. 85,7 Fum ; Leu ; SDMA ; 27-OH-C
    166 3 Ac.Ca./Am.Ac./O.St. 82,1 C8:1 ; Pro ; 27-OH-C
    167 4 B.Am./O.St. 89,2 Ac-Orn ; total DMA ; 27-OH-C ; 5a,6a-EpoxyC
    168 3 En.Met/Ac.Ca./Am.Ac. 89,8 Fum ; C5-DC (C6-OH) ; Tyr
    169 3 Ac.Ca./B.Am. 82,3 C5-DC (C6-OH) ; Carnosine ; total DMA
    170 4 En.Met/Am.Ac./O.St. 94 Fum ; Pent-P ; Tyr ; 27-OH-C
    171 3 Am.Ac./B.Am./O.St. 83,9 Pro ; SDMA ; 27-OH-C
    172 5 Ac.Ca./S.L./B.Am./P.G. 84,4 C6 (C4:1-DC) ; SM (OH) C22:2 ; Carnosine ; 8-iso-PGF2a ; LTB4
    173 4 S.L./Am.Ac./B.Am./O.St. 97,1 SM (OH) C22:2 ; Tyr; total DMA ; 27-OH-C
    174 4 Ac.Ca./B.Am./O.St. 80,2 C14:1 ; C5:1-DC ; total DMA; 27-OH-C
    175 5 Ac.Ca./Am.Ac./B.Am./O.St. 91,3 C10:2 ; C8:1 ; His ; Carnosine ; 27-OH-C
    176 4 En.Met/Ac.Ca./B.Am. 95,6 Fum ; C5:1 ; C8:1 ; total DMA
    177 4 En.Met/Ac.Ca./B.Am. 88,5 Lac ; C10:2 ; C6 (C4:1-DC); Carnosine
    178 4 Ac.Ca./S.L./Am.Ac. 81,2 C10:2 ; C5-DC (C6-OH); SM (OH) C22:2 ; Phe
    179 5 En.Met/Ac.Ca./S.L./B.Am./P.G. 82,7 OAA ; C5:1 ; SM (OH) C16:1 ; total DMA ; 8-iso-PGF2a
    180 3 En.Met/Ac.Ca./Am.Ac. 80,3 Fum ; C14:1 ; Phe
    181 3 Ac.Ca./S.L. 85,7 C5:1 ; C8:1 ; SM (OH) C22:2
    182 4 En.Met/Ac.Ca./S.L./B.Am. 89,1 Fum ; C5-DC (C6-OH) ; SM (OH) C14:1 ; Met-SO
    183 4 Ac.Ca./S.L./B.Am. 81,1 C3-DC (C4-OH) ; SM C16:0 ; SM (OH) C22:2 ; Carnosine
    184 3 En.Met/Ac.Ca./B.Am. 88,9 Fum ; C5:1 ; SDMA
    185 4 En. Met/Ac.Ca./B.Am./O.St. 80,2 Fum ; C14:1-OH ; Ac-Orn ; 27-OH-C
    186 5 S.L./Am.Ac./O.St./P.G. 94,5 SM C24:1 ; SM (OH) C16:1 ; Tyr; 27-OH-C ; 8-iso-PGF2a
    187 4 En.Met/Ac.Ca./S.L./O.St. 79,1 Fum ; C5:1 ; SM C24:1 ; 24,25-EpoxyC
    188 4 Ac.Ca./Am.Ac./O.St. 79,2 C10:2 ; C5:1 ; Met; 27-OH-C
    189 5 En.Met/Ac.Ca./B.Am. 87,5 Pent-P ; C10:2 ; C5:1 ; C8:1 ; total DMA
    190 3 En. Met/Ac.Ca./B.Am. 83,1 Fum ; C14:1 ; Carnosine
    191 3 Ac.Ca./S.L./B.Am. 79,9 C5:1 ; SM C16:1 ; Carnosine
    192 3 Ac.Ca./S.L./O.St. 80,8 C5:1 ; SM (OH) C22:2 ; 27-OH-C
    193 4 En.Met/Ac.Ca./B.Am./O.St. 87,7 Lac ; C5-DC (C6-OH) ; total DMA ; 27-OH-C
    194 3 S.L./Am.Ac./O.St. 80,4 SM (OH) C14:1 ; Thr ; 27-OH-C
    195 4 S.L./B.Am./O.St. 94,5 SM (OH) C22:2 ; Carnosine; total DMA ; 27-OH-C
    196 3 Ac.Ca./S.L./B.Am. 90,8 C5-DC (C6-OH) ; SM (OH) C22:2 ; total DMA
    197 4 En. Met/Ac.Ca./B.Am./O.St. 90,1 Fum ; CO ; Met-SO; 24,25-EpoxyC
    198 4 En.Met/S.L./B.Am./O.St. 79,4 Fum ; SM (OH) C22:1 ; Ac-Orn ; 27-OH-C
    199 4 En.Met/Ac.Ca./B.Am. 86 Pent-P ; C5:1 ; alpha-AAA ; SDMA
    200 4 En.Met/Am.Ac./B.Am./O.St. 94,3 Fum ; Tvr; SDMA ; 27-OH-C
    201 2 Ac.Ca./B.Am. 79,3 C12 ; Carnosine
    202 4 Am.Ac./B.Am./O.St. 92,8 Cit ; Tyr ; Met-SO ; 27-OH-C
    203 3 S.L./B.Am./O.St. 80,5 SM (OH) C22:2 ; SDMA ; 27-OH-C
    204 3 En. Met/Ac.Ca./P.G. 83 Fum ; C8:1 ; 8-iso-PGF2a
    205 4 En. Met/Ac.Ca./Am.Ac. 89,5 Fum;C10:2;C8:1;Tyr
    206 4 Ac.Ca./S.L./B.Am. 85,4 C5:1 ; SM C24:1 ; SDMA ; total DMA
    207 3 En.Met/Ac.Ca./B.Am. 85,5 Fum ; C5-DC (C6-OH) ; SDMA
    208 4 Ac.Ca./Am.Ac. 84,9 C10:2 ; C5-DC (C6-OH) ; Lys ; Tyr
    209 4 En.Met/Am.Ac./O.St. 79,3 Fum ; Pent-P ; Phe ; 24,25-EpoxyC
    210 5 En. Met/B.Am./O.St. 91 Fum ; Pent-P ; Carnosine ; SDMA ; 27-OH-C
    211 4 En.Met/B.Am./O.St./P.G. 81,4 Fum ; SDMA ; 24,25-EpoxyC ; TXB2
    212 3 En.Met/Am.Ac./O.St. 83,7 Fum ; Phe ; 27-OH-C
    213 3 B.Am./O.St. 82,8 Carnosine ; Met-SO ; 27-OH-C
    214 4 Ac.Ca./S.L./B.Am. 83 CO ; SM (OH) C22:2 ; Carnosine ; total DMA
    215 3 En.Met/B.Am./O.St. 84,9 Fum ; SDMA ; 27-OH-C
    216 4 En.Met/Ac.Ca./B.Am. 80,3 Fum ; C5-OH (C3-DC-M) ; Carnosine ; SDMA
    217 3 En.Met/B.Am./O.St. 85,1 Fum ; Ac-Orn ; 24,25-EpoxyC
    218 4 Ac.Ca./S.L./Am.Ac./B.Am. 92,1 C5-DC (C6-OH) ; SM (OH) C14:1 ; Phe ; total DMA
    219 5 En. Met/Am.Ac./B.Am./O.St. 91,7 Suc ; Lys ; Met-SO ; 24,25-EpoxyC ; 27-OH-C
    220 5 En. Met/Ac.Ca./B.Am. 90,9 Fum ; CO ; Met-SO; SDMA ; total DMA
    221 3 Am.Ac./O.St. 82,5 Leu ; Val ; 27-OH-C
    222 4 Ac.Ca./S.L./B.Am. 89 C5-DC (C6-OH) ; SM (OH) C16:1 ; SM (OH) C22:2 ; Carnosine
    223 4 Ac.Ca./S.L./Am.Ac./B.Am. 85 C5-DC (C6-OH) ; SM (OH) C22:2 ; Phe ; alpha-AAA
    224 5 En.Met/Ac.Ca./B.Am. 94,6 Fum ; C14:1-OH ; C5-DC (C6-OH) ; Carnosine ; Met-SO
    225 5 Ac.Ca./S.L./B.Am./O.St. 79,6 C10:2 ; C5:1 ; SM C24:1 ; Carnosine ; Cholestenone
    226 3 En.Met/B.Am. 84,2 Fum ; Ac-Orn ; SDMA
    227 4 En.Met/Ac.Ca./Am.Ac./O.St. 82,5 Fum ; C8:1 ; Thr; 27-OH-C
    228 3 En.Met/Ac.Ca./Am.Ac. 79,7 Fum ; C14:1 ; Tyr
    229 3 B.Am./O.St. 86,7 Ac-Orn ; Carnosine ; 27-OH-C
    230 4 Ac.Ca./S.L./B.Am. 89,4 C14:1 ; C5:1 ; SM (OH) C22:2 ; total DMA
    231 5 En.Met/Ac.Ca./Am.Ac./B.Am. 80,5 Lac ; C5-DC (C6-OH) ; Phe ; Carnosine; SDMA
    232 3 Am.Ac./B.Am./O.St. 86,2 Phe ; Carnosine ; 27-OH-C
    233 3 Ac.Ca./B.Am. 91,5 C10:2 ; C14:1-OH ; Carnosine
    234 5 Ac.Ca./B.Am./O.St./P.G. 80,2 C5:1 ; C8:1 ; alpha-AAA ; 3b,5a,6b-THC ; 8-iso-PGF2a
    235 4 Ac.Ca./Am.Ac./B.Am./O.St. 89,6 C8:1 ; Leu ; Met-SO ; 27-OH-C
    236 5 En.Met/Ac.Ca./S.L./B.Am. 84,1 Fum ; C3-DC (C4-OH) ; C8:1 ; SM (OH) C14:1 ; Carnosine
    237 3 En.Met/Ac.Ca./B.Am. 83,3 Fum ; C8:1 ; Met-SO
    238 4 En.Met/Ac.Ca./Am.Ac./O.St. 82,2 Fum ; C8:1 ; Ala ; 27-OH-C
    239 4 Ac.Ca./Am.Ac./B.Am. 82,6 C5-DC (C6-OH) ; C8:1 ; Leu ; Carnosine
    240 5 Ac.Ca./S.L./B.Am. 91,7 C5-DC (C6-OH) ; SM C16:1 ; SM C24:1 ; SM (OH) C22:2 ; Carnosine
    241 4 Ac.Ca./S.L./Am.Ac./O.St. 86 C5-DC (C6-OH) ; SM (OH) C22:2 ; Tyr ; 24,25-EpoxyC
    242 5 En.Met/S.L./B.Am./O.St. 89,1 Pent-P ; SM C16:0 ; Ac-Orn ; Carnosine ; 27-OH-C
    243 4 Ac.Ca./Am.Ac./B.Am. 83,7 C5-DC (C6-OH) ; Tyr ; Carnosine ; SDMA
    244 4 Ac.Ca./B.Am./O.St./P.G. 87,4 C8:1 ; Carnosine ; 27-OH-C ; LTB4
    245 4 Ac.Ca./B.Am./O.St. 86,7 C5-DC (C6-OH) ; alpha-AAA ; total DMA ; 3b,5a,6b-THC
    246 4 Ac.Ca./S.L./B.Am./O.St. 95,5 C5-DC (C6-OH) ; SM C26:0 ; Met-SO ; 27-OH-C
    247 4 Ac.Ca./B.Am./O.St. 86 C10:2 ; C14:1 ; Camosine ; 27-OH-C
    248 5 Ac.Ca./S.L./B.Am. 86,8 C5:1 ; C8:1 ; SM C16:1 ; alpha-AAA ; Met-SO
    249 4 Ac.Ca./S.L./B.Am. 91,7 C5-DC (C6-OH) ; SM C16:0; Carnosine ; total DMA
    250 3 S.L./B.Am./O.St. 86,9 SM (OH) C14:1 ; Carnosine ; 27-OH-C
    251 3 Ac.Ca./B.Am. 83,4 C10:2 ; C8:1 ; Carnosine
    252 4 Ac.Ca./S.L./B.Am. 87,2 C5-DC (C6-OH) ; SM C18:1 ; SM (OH) C16:1 ; total DMA
    253 4 Ac.Ca./B.Am. 79,3 C6 (C4:1-DC) ; alpha-AAA ; Carnosine; total DMA
    254 3 Am.Ac./B.Am./O.St. 88,1 Leu; Carnosine ; 27-OH-C
    255 4 En.Met/Am.Ac./B.Am./O.St. 93,2 Fum ; Pro ; total DMA ; 27-OH-C
    256 3 En.Met/Ac.Ca./B.Am. 85,5 Fum ; C14:1 ; total DMA
    257 4 En.Met/Ac.Ca./B.Am./O.St. 89,2 Fum ; C14:2-OH ; Ac-Orn ; 27-OH-C
    258 4 En.Met/Ac.Ca./S.L./B.Am. 81,6 Fum ; C3-DC (C4-OH) ; SM (OH) C14:1 ; Carnosine
    259 4 Ac.Ca./Am.Ac./O.St. 82,9 C5-DC (C6-OH) ; Phe ; Tyr ; 24,25-EpoxyC
    260 4 En.Met/Am.Ac./B.Am./O.St. 93,4 Fum ; Trp ; total DMA ; 27-OH-C
    261 3 Ac.Ca./Am.Ac./B.Am. 83,5 C5-DC (C6-OH) ; Tyr ; alpha-AAA
    262 4 En.Met/Ac.Ca./B.Am. 88,8 Fum ; C5-DC (C6-OH) ; Carnosine ; SDMA
    263 5 En.Met/Ac.Ca./Am.Ac./B.Am./O.St. 87,6 Pent-P ; C10:2 ; Lys ; Ac-Orn ; 27-OH-C
    264 5 En.Met/Ac.Ca./Am.Ac./B.Am./O.St. 87 Lac ; C6 (C4:1-DC) ; Phe ; Carnosine ; 24,25-EpoxyC
    265 3 Ac.Ca./S.L./B.Am. 86,4 C5:1 ; SM C16:0 ; total DMA
    266 4 En.Met/B.Am./O.St. 88,7 Fum ; Pent-P ; SDMA ; 27-OH-C
    267 4 Ac.Ca./Am.Ac. 87,8 C10:2 ; C5-DC (C6-OH) ; Lys ; Phe
    268 5 Ac.Ca./S.L./B.Am./P.G. 79,5 C10:2 ; C14:1 ; SM (OH) C14:1 ; Met-SO ; DHA
    269 4 Ac.Ca./Am.Ac./B.Am. 91,3 C10:2; C5-DC (C6-OH) ; Tyr ; total DMA
    270 4 Ac.Ca./S.L./B.Am./O.St. 82,3 C10:2 ; SM (OH) C22:1 ; Carnosine ; 27-OH-C
    271 3 Ac.Ca./Am.Ac./O.St. 80,7 C8:1 ; Ala ; 27-OH-C
    272 4 En.Met/Ac.Ca./B.Am./P.G. 83,9 Fum ; C8:1 ; Carnosine ; LTB4
    273 5 En.Met/Ac.Ca./S.L. 82,3 Fum ; Pent-P ; C14:1-OH ; SM C26:1 ; SM (OH) C22:2
    274 5 En.Met/Ac.Ca./Am.Ac. 84,4 Pent-P ; Suc ; C10:2 ; C5-DC (C6-OH) ; Tyr
    275 3 Am.Ac./B.Am./O.St. 82 Leu ; SDMA ; 27-OH-C
    276 6 Ac.Ca./S.L./Am.Ac./P.G. 86,2 C10:2 ; C5-DC (C6-OH) ; SM (OH) C14:1 ; SM (OH) C22:2 ; Tyr ; DHA
    277 4 En. Met/Ac.Ca./Am.Ac./O.St. 95,1 Fum ; C10:2 ; Tyr ; 27-OH-C
    278 5 En.Met/Ac.Ca./O.St. 82,8 Fum ; C8:1 ; 24-DH-Lanosterol ; Cholestenone ; 3b,5a,6b-THC
    279 4 En.Met/Ac.Ca. 80,8 Fum ; C14:1 ; C5:1 ; C8:1
    280 4 Ac.Ca./S.L./B.Am. 93,8 C5-DC (C6-OH) ; SM (OH) C14:1 ; Carnosine ; total DMA
    281 3 Ac.Ca./B.Am./O.St. 87,9 C4:1 ; Met-SO; 27-OH-C
    282 4 En.Met/Ac.Ca./Am.Ac. 84,3 Fum ; Pent-P ; C10:2 ; Tyr
    283 3 En.Met/Ac.Ca./B.Am. 80,4 Fum ; C14:1-OH ; SDMA
    284 4 Ac.Ca./S.L./B.Am. 91 C5:1 ; SM (OH) C14:1 ; Carnosine ; SDMA
    285 4 En.Met/Ac.Ca./Am.Ac./O.St. 94,1 Fum ; C8:1 ; Tyr; 27-OH-C
    286 4 En.Met/B.Am./O.St. 82,2 Fum ; Lac; Met-SO ; 24,25-EpoxyC
    287 4 En.Met/Am.Ac./B.Am. 83,7 Fum ; Suc ; Ile ; Met-SO
    288 5 Ac.Ca./B.Am./O.St. 85,1 C5:1 ; Ac-Orn ; SDMA ; 24,25-EpoxyC ; Cholestenone
    289 4 En.Met/Ac.Ca./Am.Ac./O.St. 79,2 Fum ; C14:1 ; Ala ; 27-OH-C
    290 5 Ac.Ca./S.L./O.St. 79,1 C5:1 ; C8:1 ; SM (OH) C22:2 ; 24-DH-Lanosterol ; 5a,6a-EpoxyC
    291 4 En.Met/Am.Ac./B.Am./O.St. 86,5 Fum ; Leu ; Ac-Orn ; 27-OH-C
    292 4 En.Met/Ac.Ca./B.Am. 84,6 Fum ; C14:1-OH ; Met-SO ; SDMA
    293 4 En.Met/Ac.Ca./Am.Ac./B.Am. 98,4 Fum ; C5-DC (C6-OH) ; Tyr ; total DMA
    294 5 En.Met/Ac.Ca./Am.Ac./O.St./P.G. 81,2 Fum ; C5-DC (C6-OH) ; Thr ; 27-OH-C ; LTB4
    295 3 Am.Ac./O.St. 86,1 Cit ; Met; 27-OH-C
    296 3 En.Met/Ac.Ca./B.Am. 83,6 Fum ; C6 (C4:1-DC) ; Ac-Orn
    297 4 Ac.Ca./B.Am. 80,1 C14:1 ; C5:1 ; alpha-AAA ; Carnosine
    298 4 Ac.Ca./Am.Ac. 85,8 C10:2 ; C5-DC (C6-OH) ; Tyr ; Val
    299 5 En.Met/Ac.Ca./B.Am. 90,1 Fum ; C10:2 ; C14:1 ; C14:1-OH ; Carnosine
    300 4 Ac.Ca./S.L./B.Am. 84,1 C5:1 ; SM C24:1 ; aipha-AAA ; total DMA
    301 4 En.Met/Ac.Ca./B.Am./O.St. 83,2 Fum ; C8:1 ; SDMA ; 27-OH-C
    302 5 En.Met/B.Am./O.St. 82,5 Suc ; alpha-AAA ; Carnosine ; SDMA ; 3b,5a,6b-THC
    303 3 B.Am./O.St. 82,2 Ac-Orn ; alpha-AAA ; 27-OH-C
    304 5 En.Met/Ac.Ca./B.Am./O.St. 88,5 Fum ; C14:1-OH ; Carnosine ; SDMA ; 3b,5a,6b-THC
    305 3 Ac.Ca./Am.Ac./O.St. 82 C10:2 ; Val ; 27-OH-C
    306 3 B.Am./O.St./P.G. 79,3 Carnosine ; 27-OH-C ; 8-iso-PGF2a
    307 4 Ac.Ca./B.Am./P.G. 88,7 C10:2 ; C14:1-OH ; Carnosine ; 8-iso-PGF2a
    308 4 En.Met/Ac.Ca./B.Am. 84,7 Fum ; C18:1 ; Carnosine ; total DMA
    309 4 Ac.Ca./S.L./B.Am. 90,2 C14:1 ; C5:1 ; SM C16:0 ; Carnosine
    310 4 Ac.Ca./B.Am./O.St. 90,6 C14:1 ; Carnosine ; Met-SO ; 27-OH-C
    311 4 En.Met/B.Am./O.St. 85 Fum ; SDMA ; 25-OH-C ; 27-OH-C
    312 3 En.Met/Ac.Ca./Am.Ac. 82,8 Fum ; C8:1 ; Tyr
    313 4 Am.Ac./B.Am./O.St. 91,7 Phe ; SDMA ; total DMA ; 27-OH-C
    314 4 Ac.Ca./S.L./B.Am. 79,6 C6 (C4:1-DC) ; SM (OH) C14:1 ; SM (OH) C22:2 ; Carnosine
    315 4 Ac.Ca./S.L./B.Am. 82 C5:1 ; SM C16:0; alpha-AAA ; total DMA
    316 3 B.Am./O.St. 87,7 Met-SO ; 27-OH-C ; 5a,6a-EpoxyC
    317 5 En.Met/Ac.Ca./Am.Ac./P.G. 81,4 Fum ; CO ; C10:2 ; Tyr ; 8-iso-PGF2a
    318 4 En.Met/B.Am./O.St. 89,8 Fum ; SDMA ; 27-OH-C ; 3b,5a,6b-THC
    319 4 En. Met/Ac.Ca./B.Am. 86,5 Pent-P ; C10:2 ; C8:1 ; Carnosine
    320 4 En.Met/Ac.Ca./B.Am. 88 Fum ; C3-DC (C4-OH) ; Carnosine ; total DMA
    321 3 Ac.Ca./Am.Ac./O.St. 79,9 C10:2 ; Thr ; 27-OH-C
    322 4 En.Met/Ac.Ca./B.Am./O.St. 90,2 Fum ; C5:1 ; SDMA ; 27-OH-C
    323 4 En.Met/Am.Ac./O.St. 84,1 Fum ; Pent-P ; Phe ; 27-OH-C
    324 5 En.Met/Ac.Ca./B.Am. 92,9 Fum ; C14:1-OH ; C5:1 ; Carnosine ; total DMA
    325 4 Ac.Ca./Am.Ac./B.Am. 93,5 C10:2 ; C6 (C4:1-DC) ; Phe ; Carnosine
    326 4 Ac.Ca./B.Am. 88,8 C5:1 ; C8:1 ; alpha-AAA ; total DMA
    327 5 Ac.Ca./S.L./B.Am. 90 C5:1 ; SM C16:0 ; SM (OH) C22:2 ; Carnosine ; SDMA
    328 3 Ac.Ca./S.L./B.Am. 84,3 C5:1 ; SM C16:1 ; total DMA
    329 3 B.Am./O.St. 85,1 Met-SO; SDMA; 27-OH-C
    330 4 En.Met/Ac.Ca./B.Am./O.St. 81,1 Fum ; C5:1 ; Met-SO ; Cholestenone
    331 4 En.Met/Ac.Ca./Am.Ac. 93,1 Fum ; C10:2 ; C5-DC (C6-OH) ; Tyr
    332 5 Ac.Ca./B.Am./O.St. 87 C5:1 ; C8:1 ; Ac-Orn ; Total DMA ; 24,25-EpoxyC
    333 4 Ac.Ca./S.L./B.Am. 89,1 C10:2 ; C5:1 ; SM C24:1 ; total DMA
    334 5 Ac.Ca./S.L./B.Am. 83,9 C5-DC (C6-OH) ; C6:1 ; SM C26:0 ; SM (OH) C14:1 ; Met-SO
    335 4 Ac.Ca./S.L./B.Am./O.St. 91,2 C5:1 ; SM C24:1 ; total DMA ; 24,25-EpoxyC
    336 4 En.Met/Ac.Ca./Am.Ac./O.St. 86,5 Fum ; C14:1 ; Tyr ; 25-OH-C
    337 4 Ac.Ca./B.Am. 82,1 C5-DC (C6-OH) ; Carnosine ; SDMA ; total DMA
    338 5 Ac.Ca./S.L./B.Am. 82,3 C10:2 ; C2 ; SM (OH) C14:1 ; Carnosine ; total DMA
    339 4 Ac.Ca./B.Am./P.G. 81,7 C10:2 ; C5:1 ; total DMA ; 8-iso-PGF2a
    340 4 Ac.Ca./S.L./B.Am./O.St. 94,1 C8:1 ; SM C26:0 ; Met-SO ; 27-OH-C
    341 4 En. Met/B.Am./O.St. 92,7 Fum ; Ac-Orn ; SDMA ; 27-OH-C
    342 4 S.L./B.Am./O.St. 85,8 SM (OH) C22:2 ; Ac-Orn ; SDMA ; 27-OH-C
    343 4 En. Met/B.Am./O.St. 94,4 Fum ; Met-SO ; 27-OH-C ; 5a,6a-EpoxyC
    344 4 En. Met/Ac.Ca./B.Am. 87,1 Fum ; C10:2 ; C14:1-OH ; Ac-Orn
    345 4 En.Met/Am.Ac./B.Am./O.St. 95,2 Fum ; Asp ; Carnosine ; 27-OH-C
    346 4 En.Met/Am.Ac./O.St. 84,9 Fum ; Asn ; Phe ; 27-OH-C
    347 3 Am.Ac./B.Am./O.St. 92,2 Val ; total DMA ; 27-OH-C
    348 5 S.L./B.Am./O.St. 84,6 SM C26:1 ; SM (OH) C22:2 ; Ac-Orn ; 24,25-EpoxyC ; 27-OH-C
    349 4 Ac.Ca./S.L./Am.Ac./B.Am. 84,7 C5-DC (C6-OH) ; SM (OH) C14:1 ; Phe ; SDMA
    350 5 Ac.Ca./S.L./B.Am./O.St. 89,9 C5:1-DC ; SM (OH) C14:1; SDMA ; total DMA ; 27-OH-C
    351 4 En.Met/Ac.Ca./S.L./B.Am. 90,8 Fum ; C5:1 ; SM (OH) C22:2 ; SDMA
    352 4 Ac.Ca./S.L./Am.Ac./B.Am. 83,4 C5-DC (C6-OH) SM (OH) C22:2 ; Lys ; SDMA
    353 4 En.Met/B.Am./O.St. 90 Fum ; Suc ; SDMA ; 27-OH-C
    354 4 En.Met/Ac.Ca./B.Am./O.St. 95,6 Fum ; C5:1-DC ; total DMA ; 27-OH-C
    355 4 Ac.Ca./Am.Ac./B.Am./O.St. 85,3 C14:1 ; Phe ; Carnosine ; 27-OH-C
    356 5 Ac.Ca./S.L./B.Am. 81,3 C10:2 ; C5:1 ; SM C24:1 ; SM (OH) C14:1 ; Carnosine
    357 3 B.Am./O.St. 85,7 Carnosine ; 24-DH-Lanosterol ; 27-OH-C
    358 4 Ac.Ca./S.L./B.Am./O.St. 94,8 C5:1 ; SM C16:0 ; total DMA ; 27-OH-C
    359 4 S.L./Am.Ac./B.Am./O.St. 82,6 SM (OH) C22:2 ; Pro ; SDMA ; 27-OH-C
    360 4 En.Met/B.Am./O.St. 96,3 Fum ; Met-SO ; SDMA ; 27-OH-C
    361 4 S.L./B.Am./O.St. 89,7 SM (OH) C22:2 ; Met-SO ; 27-OH-C ; 5a,6a-EpoxyC
    362 4 En.Met/Ac.Ca./S.L. 85,4 Fum ; C5:1 ; C8:1 ; SM (OH) C22:2
    363 3 En.Met/B.Am./O.St. 94 Fum ; Met-SO ; 27-OH-C
    364 4 B.Am./O.St. 79,1 Ac-Orn ; SDMA ; 27-OH-C ; 3b,5a,6b-THC
    365 5 En.Met/Ac.Ca./Am.Ac./B.Am. 84,8 Fum ; C3-DC (C4-OH) ; Phe ; Carnosine ; SDMA
    366 4 Ac.Ca./S.L./Am.Ac./B.Am. 88,6 C5-DC (C6-OH) ; SM (OH) C22:2 ; Lys ; Carnosine
    367 4 En.Met/Ac.Ca./S.L. 81 Fum ; C14:1 ; C5:1 ; SM (OH) C22:2
    368 4 En.Met/Ac.Ca./B.Am./O.St. 82,8 Lac; C14:1 ; Carnosine ; 27-OH-C
    369 4 Ac.Ca./S.L./B.Am. 83,5 C3-DC (C4-OH) ; SM C16:1 ; SM (OH) C22:2 ; Carnosine
    370 4 B.Am./O.St. 87,5 Ac-Orn ; Carnosine ; SDMA ; 27-OH-C
    371 4 Ac.Ca./Am.Ac./B.Am. 82,1 C5-DC (C6-OH) ; Lys ; alpha-AAA ; total DMA
    372 4 Ac.Ca./S.L./B.Am./O.St. 79,8 C10:2 ; SM (OH) C14:1 ; total DMA ; 3b,5a,6b-THC
    373 5 Ac.Ca./S.L./Am.Ac./B.Am. 85,1 C5-DC (C6-OH); SM C26:0 ; SM (OH) C14:1 ; Phe ; total DMA
    374 5 En.Met/Ac.Ca./Am.Ac./O.St. 80,2 Pent-P ; C10:2 ; C8:1 ; Phe ; 24,25-EpoxyC
    375 3 En.Met/B.Am./O.St. 87,2 Fum ; SDMA ; 3b,5a,6b-THC
    376 4 S.L./B.Am./O.St. 88,5 SM C26:0 ; Ac-Orn ; 24,25-EpoxyC ; 27-OH-C
    377 3 S.L./Am.Ac./O.St. 88,4 SM (OH) C14:1 ; Phe ; 27-OH-C
    378 4 Ac.Ca./Am.Ac./B.Am./O.St. 79,4 C5-DC (C6-OH) ; Val ; Met-SO; 27-OH-C
    379 5 Ac.Ca./S.L./B.Am. 85,1 C5 ; C5:1 ; C6 (C4:1-DC) ; SM (OH) C22:2 ; Carnosine
    380 4 Ac.Ca./B.Am./O.St./P.G. 85,7 C8:1 ; Carnosine ; 27-OH-C ; 8-iso-PGF2a
    381 4 Ac.Ca./B.Am. 84,4 C10:2 ; C14:1-OH ; alpha-AAA ; Carnosine
    382 4 Ac.Ca./B.Am./O.St. 81,4 C5:1-DC ; Ac-Orn ; 24,25-EpoxyC ; 27-OH-C
    383 4 Ac.Ca./S.L./B.Am./O.St. 79,8 C8:1 ; SM C26:0 ; Ac-Orn ; 27-OH-C
    384 4 Ac.Ca./B.Am. 82,4 C4:1 ; C5:1 ; alpha-AAA ; total DMA
    385 4 En.Met/Am.Ac./O.St. 86,1 Fum ; Leu ; Phe ; 27-OH-C
    386 5 Ac.Ca./S.L./Am.Ac./B.Am. 90,1 C5-DC (C6-OH) ; SM (OH) C16:1 ; SM (OH) C22:2 ; Tyr; Carnosine
    387 3 En.Met/Ac.Ca./B.Am. 82,6 Fum ; C5-DC (C6-OH) ; Met-SO
    388 4 Ac.Ca./S.L./B.Am. 84,3 C5-DC (C6-OH) ; SM C16:0 ; SM (OH) C22:1 ; Carnosine
    389 4 Ac.Ca./S.L./Am.Ac. 81,2 C5-DC (C6-OH) ; SM C24:1 ; SM (OH) C14:1 ; Tyr
    390 4 Ac.Ca./S.L./B.Am./P.G. 85,9 C2 ; SM (OH) C22:2 ; Carnosine ; 8-iso-PGF2a
    391 4 En.Met/Am.Ac./B.Am./O.St. 82 Pent-P ; Leu ; Ac-Orn ; 27-OH-C
    392 4 En.Met/Ac.Ca./S.L./O.St. 80,1 Fum ; C10 ; SM (OH) C22:2 ; 27-OH-C
    393 4 En.Met/Ac.Ca./B.Am. 84,2 Fum ; C5 ; SDMA ; total DMA
    394 4 Ac.Ca./S.L./B.Am./O.St. 81,1 C5:1 ; SM C16:1 ; SDMA ; 3b,5a,6b-THC
    395 4 En.Met/Ac.Ca./B.Am. 88,8 Fum ; C5:1 ; C8:1 ; Met-SO
    396 5 Ac.Ca./B.Am./P.G. 82 C10:2 ; C8:1 ; Carnosine ; 8-iso-PGF2a ; LTB4
    397 4 Ac.Ca./S.L./B.Am./O.St. 86,7 C5:1-DC ; SM (OH) C14:1 ; SDMA ; 27-OH-C
    398 4 En.Met/Ac.Ca./S.L./B.Am. 88,6 Fum ; C2 ; SM (OH) C22:2 ; total DMA
    399 6 Ac.Ca./Am.Ac./B.Am./O.St./P.G. 81,2 C10:2 ; C14:1 ; Phe ; total DMA ; 5a,6a-EpoxyC ; 8-iso-PGF2a
    400 4 En. Met/Ac.Ca./B.Am. 94,8 Fum ; C14:1 ; C5:1 ; total DMA
    401 5 En.Met/Ac.Ca./B.Am. 92,3 Fum ; C0; C10:2 ; Met-SO ; total DMA
    402 5 En.Met/Ac.Ca./S.L./O.St. 83,5 Pent-P ; C5:1 ; SM C16:1 ; 24,25-EpoxyC ; 3b,5a,6b-THC
    403 5 Ac.Ca./B.Am./O.St. 81 C14:1 ; C5:1 ; alpha-AAA ; Met-SO ; Cholestenone
    404 4 Ac.Ca./B.Am. 88,1 C0 ; C5-DC (C6-OH) ; alpha-AAA ; Met-SO
    405 4 S.L./Am.Ac./O.St. 83 SM C26:1 ; SM (OH) C22:2 ; Leu ; 27-OH-C
    406 4 En.Met/Am.Ac./B.Am./O.St. 93,6 Fum ; Val ; total DMA ; 27-OH-C
    407 4 Ac.Ca./S.L./B.Am. 89,3 C5-DC (C6-OH) ; SM (OH) C22:2 ; alpha-AAA ; Carnosine
    408 4 En.Met/Ac.Ca./O.St. 79,3 Fum ; C14:2-OH ; 24-DH-Lanosterol ; 27-OH-C
    409 4 En.Met/Am.Ac./B.Am./O.St. 93,5 Fum ; Phe ; SDMA ; 27-OH-C
    410 4 En.Met/Am.Ac./B.Am. 80,7 Fum ; Tyr ; Val ; total DMA
    411 5 Ac.Ca./Am.Ac./O.St./P.G. 88,4 C6 (C4:1-DC) ; Phe ; 27-OH-C ; 8-iso-PGF2a ; LTB4
    412 4 Ac.Ca./S.L./B.Am. 88,6 C5-DC (C6-OH) ; C8:1 ; SM (OH) C22:2 ; Carnosine
    413 5 En.Met/Ac.Ca./S.L./B.Am. 95,3 Suc ; C14:2-OH ; C5-DC (C6-OH) ; SM C26:0 ; total DMA
    414 4 Ac.Ca./B.Am. 85,8 C5-OH (C3-DC-M) ; C5-DC (C6-OH) ; alpha-AAA ; Met-SO
    415 3 Ac.Ca./B.Am./O.St. 81,8 C5:1 ; total DMA ; Cholestenone
    416 4 En.Met/B.Am./O.St. 95,1 Fum ; Lac; Met-SO; 27-OH-C
    417 5 Ac.Ca./Am.Ac./B.Am./O.St. 92,5 C10:2 ; C8:1 ; Met; Carnosine ; 27-OH-C
    418 3 En.Met/B.Am./O.St. 85,8 Fum ; total DMA ; 3b,5a,6b-THC
    419 3 Ac.Ca./S.L./B.Am. 79,1 C3-DC (C4-OH) ; SM (OH) C22:2 ; Carnosine
    420 4 En.Met/B.Am./O.St. 89,1 Fum ; SDMA ; total DMA ; 3b,5a,6b-THC
    421 5 En.Met/Ac.Ca./S.L./B.Am. 81,2 Fum ; C3-DC (C4-OH) ; SM (OH) C14:1 ; Carnosine ; Met-SO
    422 4 En.Met/Am.Ac./O.St. 94 Fum ; Tyr ; 27-OH-C ; 5a,6a-EpoxyC
    423 5 Ac.Ca./S.L./B.Am. 85,2 C5:1 ; C5-DC (C6-OH) ; SM (OH) C22:2 ; alpha-AAA ; SDMA
    424 5 En.Met/Ac.Ca./B.Am. 91,2 Fum ; Pent-P ; C10:2; C14:1 ; Carnosine
    425 4 Ac.Ca./Am.Ac./B.Am./O.St. 83,7 C10:2 ; Met; total DMA ; 27-OH-C
    426 5 Ac.Ca./B.Am. 82,1 C14:1 ; C14:2-OH ; C5-DC (C6-OH) ; Carnosine ; total DMA
    427 4 S.L./B.Am./O.St. 91,6 SM C26:0 ; Met-SO ; SDMA ; 27-OH-C
    428 4 En.Met/B.Am./O.St. 95,2 Fum ; total DMA ; 27-OH-C ; 3b,5a,6b-THC
    429 3 Ac.Ca./Am.Ac./O.St. 82,3 C8:1 ; Val ; 27-OH-C
    430 4 Ac.Ca./S.L./Am.Ac./B.Am. 80,2 C5-DC (C6-OH) ; SM (OH) C14:1 ; Phe ; alpha-AAA
    431 4 Ac.Ca./Am.Ac./O.St. 83,9 C10:2; Met; 27-OH-C ; 5a,6a-EpoxyC
    432 5 En.Met/Ac.Ca./S.L./B.Am./O.St. 93,8 Fum ; C5-DC (C6-OH) ; SM C16:1 ; Met-SO ; Cholestenone
    433 4 En.Met/Ac.Ca./O.St. 81,1 Fum ; C14:1 ; 24S-OH-C ; 27-OH-C
    434 4 En.Met/Am.Ac./O.St. 93,6 Fum ; Tyr ; 27-OH-C ; Cholestenone
    435 6 Ac.Ca./Am.Ac./B.Am. 85,9 C0 ; C14:1 ; C5-DC (C6-OH) ; Cit; Met-SO ; total DMA
    436 4 Ac.Ca./Am.Ac./B.Am./O.St. 92,3 C6:1 ; Lys ; total DMA ; 27-OH-C
    437 4 En. Met/Am.Ac./O.St./P.G. 92,9 Fum ; Phe ; 27-OH-C ; 8-iso-PGF2a
    438 5 Ac.Ca./Am.Ac./B.Am./O.St. 85,7 C5-DC (C6-OH) ; Arq ; SDMA ; total DMA ; 27-OH-C
    439 3 Ac.Ca./S.L./B.Am. 80,5 C0 ; SM (OH) C22:2 ; total DMA
    440 5 Ac.Ca./S.L./B.Am./O.St. 86,4 C10:2 ; C8:1 ; SM (OH) C14:1 ; Carnosine ; 27-OH-C
    441 5 Ac.Ca./B.Am./O.St. 80,6 C16:2 ; C5-DC (C6-OH) ; C8:1 ; Met-SO ; 27-OH-C
    442 4 S.L./Am.Ac./B.Am./O.St. 79,6 SM (OH) C22:2 ; Cit ; Ac-Orn ; 27-OH-C
    443 3 Am.Ac./B.Am./O.St. 82 Pro ; Carnosine ; 27-OH-C
    444 5 Ac.Ca./S.L./B.Am./O.St. 81,2 C5:1 ; SM C24:1 ; SM (OH) C22:1 ; Carnosine ; 24,25-EpoxyC
    445 5 Ac.Ca./S.L./B.Am. 82,5 C5-DC (C6-OH) ; SM C16:1 ; SM C24:0 ; SM (OH) C22:1 ; Carnosine
    446 4 En.Met/Ac.Ca.lAm.Ac./B.Am. 95,9 Fum ; C5-DC (C6-OH) ; Tyr ; SDMA
    447 5 En.Met/Ac.Ca./S.L./B.Am. 87,4 Lac ; Pent-P ; C3-DC (C4-OH) ; SM C16:1 ; Carnosine
    448 4 Ac.Ca./S.L./B.Am. 81,8 C14:2-OH; C5-DC (C6-OH) ; SM (OH) C14:1 ; total DMA
    449 5 Ac.Ca./S.L./Am.Ac./B.Am. 80,4 C5:1 ; SM C16:1 ; Cit ; Met-SO ; total DMA
    450 4 Ac.Ca./S.L./B.Am./O.St. 95 C5:1 ; SM (OH) C14:1 ; total DMA ; 27-OH-C
    451 4 Ac.Ca./Am.Ac./B.Am./O.St. 89,7 C0 ; Cit ; Met-SO ; 27-OH-C
    452 4 Ac.Ca./B.Am./O.St./P.G. 87,8 C14:1 ; Carnosine ; 27-OH-C ; 8-iso-PGF2a
    453 3 S.L./B.Am./O.St. 82,6 SM (OH) C22:1 ; Carnosine ; 27-OH-C
    454 4 En.Met/Am.Ac./B.Am./O.St. 93,8 Fum ; Tyr ; Carnosine ; 27-OH-C
    455 4 Ac.Ca./Am.Ac./B.Am./O.St. 82,9 C10:2 ; Pro ; Carnosine ; 27-OH-C
    456 6 Ac.Ca./S.L./Am.Ac./B.Am./O.St. 91,8 C14:2-OH ; C5-DC (C6-OH) ; SM (OH) C22:2 ; Phe ; SDMA ; 27-OH-C
    457 5 En.Met/Ac.Ca./S.L./B.Am. 87 Fum ; C3-DC (C4-OH) ; C4:1 ; SM (OH) C22:2 ; Met-SO
    458 4 En.Met/Ac.Ca./B.Am./O.St. 94,6 Fum ; C5:1-DC ; SDMA ; 27-OH-C
    459 4 En.Met/B.Am./O.St. 81,3 Pent-P ; alpha-AAA ; Carnosine ; 27-OH-C
    460 4 Ac.Ca./S.L./B.Am. 86,2 C5:1 ; SM C16:1 ; Carnosine ; SDMA
    461 4 En.Met/Ac.Ca./B.Am. 90,3 Fum ; C2 ; Carnosine ; total DMA
    462 5 En.Met/Ac.Ca./S.L./B.Am. 88,4 Pent-P ; C10:2 ; C6 (C4:1-DC) ; SM (OH) C22:2 ; Carnosine
    463 4 En.Met/Ac.Ca./B.Am./P.G. 80,1 Lac; C8:1 ; Carnosine ; LTB4
    464 4 S.L./B.Am./O.St. 89,7 SM (OH) C22:2 ; Met-SO ; SDMA ; 27-OH-C
    465 4 En.Met/Ac.Ca./B.Am. 82,5 Lac ; C10:2 ; C8:1 ; Carnosine
    466 4 Ac.Ca./B.Am./P.G. 82,2 C10:2 ; C6 (C4:1-DC) ; Carnosine ; LTB4
    467 4 Ac.Ca./S.L./B.Am./O.St. 91,2 C10:2 ; SM C26:0 ; Met-SO ; 27-OH-C
    468 4 Ac.Ca./S.L./Am.Ac./B.Am. 84,6 C5-DC (C6-OH) ; SM C16:1 ; Lys ; total DMA
    469 5 Ac.Ca./S.L./B.Am./O.St. 90,4 C5:1 ; SM C24:1 ; Carnosine ; 24,25-EpoxyC ; Cholestenone
    470 4 En.Met/Ac.Ca./B.Am. 87,4 Fum ; C10:2 ; C14:1 ; Carnosine
    471 6 Ac.Ca./B.Am./O.St./P.G. 92 C5:1 ; C8:1 ; SDMA ; total DMA ; 5a,6a-EpoxyC; LTB4
    472 4 En. Met/Ac.Ca./B.Am./O.St. 94,5 Fum ; C8:1 ; Met-SO ; 27-OH-C
    473 4 En.Met/Ac.Ca./Am.Ac. 87,7 Lac ; Pent-P ; C8:1 ; Cit
    474 4 En.Met/Am.Ac./O.St./P.G. 80,7 Fum ; Val ; 27-OH-C ; 8-iso-PGF2a
    475 4 En.Met/Ac.Ca./B.Am./O.St. 94,6 Fum ; C4:1 ; Met-SO ; 27-OH-C
    476 4 En.Met/Ac.Ca./B.Am. 81,4 Fum ; C18:1 ; Carnosine ; SDMA
    477 4 En.Met/S.L./Am.Ac./O.St. 87,5 Fum ; SM (OH) C22:2 ; Phe ; 27-OH-C
    478 5 Ac.Ca./S.L./B.Am. 83,4 C5-DC (C6-OH) ; C6:1 ; SM C16:0 ; Carnosine ; SDMA
    479 6 En.Met/Ac.Ca./S.L./B.Am./O.St./P.G. 81,2 Fum ; C5:1 ; SM C16:1 ; Met-SO ; 24-DH-Lanosterol ; DHA
    480 5 En.Met/Ac.Ca./S.L./O.St. 79,6 Pent-P ; C10:2 ; C5:1 ; SM (OH) C14:1 ; 24,25-EpoxyC
    481 4 En.Met/Ac.Ca./S.L./Am.Ac. 83,2 Fum ; C5-DC (C6-OH) ; SM (OH) C22:2 ; Phe
    482 5 En.Met/Ac.Ca./S.L./B.Am. 87,3 Fum ; C5-DC (C6-OH) ; SM (OH) C14:1 ; Ac-Orn ; SDMA
    483 5 Ac.Ca./S.L./Am.Ac./B.Am. 80,3 C0 ; SM C24:1 ; SM (OH) C22:2 ; Cit ; total DMA
    484 4 Ac.Ca./S.L./Am.Ac./B.Am. 79,7 C5-DC (C6-OH) ; SM C16:1 ; Phe ; alpha-AAA
    485 4 B.Am./O.St. 90,5 Ac-Orn ; Carnosine ; 24,25-EpoxyC ; 27-OH-C
    486 4 Ac.Ca./Am.Ac./O.St. 89,8 C5-DC (C6-OH) ; Cit ; Tyr ; 27-OH-C
    487 4 En.Met/Am.Ac./O.St. 83,6 Fum ; Lac ; Phe ; 27-OH-C
    488 4 Ac.Ca./S.L./B.Am. 85,3 C5-DC (C6-OH) ; SM C16:0 ; alpha-AAA ; Met-SO
    489 5 Ac.Ca./B.Am. 80,9 C10:2 ; C14:1 ; C4:1 ; C5:1 ; Met-SO
    490 3 S.L./B.Am./O.St. 86,3 SM C24:1 ; Carnosine ; 27-OH-C
    491 4 En.Met/Ac.Ca./S.L. 82,8 Pent-P ; C5:1 ; C8:1 ; SM (OH) C22:2
    492 5 En.Met/Ac.Ca./S.L./B.Am. 90,4 Fum ; C5-DC (C6-OH) ; SM C16:1 ; Ac-Orn ; SDMA
    493 4 En.Met/Ac.Ca. 79,9 Fum ; Pent-P ; Suc ; C14:1
    494. 4 S.L./B.Am./O.St. 84,9 SM (OH) C22:2 ; Ac-Orn ; alpha-AAA ; 27-OH-C
    495 5 Ac.Ca./S.L./Am.Ac./B.Am./O.St. 85 C5-DC (C6-OH) ; SM (OH) C22:2 ; Ala ; SDMA ; 27-OH-C
    496 3 Ac.Ca./S.L./B.Am. 79 C5:1 ; SM C24:1 ; SDMA
    497 4 En.Met/B.Am./O.St. 90,2 Lac ; Carnosine ; 24-DH-Lanosterol ; 27-OH-C
    498 4 En.Met/Ac.Ca./S.L./B.Am. 81 Lac ; C2 ; SM (OH) C22:2 ; Carnosine
    499 4 En.Met/B.Am./O.St./P.G. 81,5 Fum ; Ac-Orn ; 27-OH-C ; DHA
    500 4 Ac.Ca./B.Am./O.St. 81,8 C10:2 ; Carnosine ; 24-DH-Lanosterol ; 27-OH-C
    501 4 En.Met/Ac.Ca./B.Am. 84 Fum ; Suc ; C14:1 ; SDMA
    502 4 En.Met/Ac.Ca./B.Am. 90,7 Fum ; Suc ; C14:1 ; Carnosine
    503 4 En.Met/Am.Ac./B.Am./O.St. 95,2 Fum ; Tyr; Met-SO ; 27-OH-C
    504 4 Ac.Ca./S.L./O.St. 84 C5:1-DC ; SM (OH) C22:2 ; 24,25-EpoxyC ; 27-OH-C
    505 4 En.Met/Am.Ac./O.St. 91,7 Fum ; Phe ; 24-DH-Lanosterol ; 27-OH-C
    506 4 En.Met/Ac.Ca./B.Am. 81,9 Fum ; C0 ; C5:1 ; Met-SO
    507 4 Ac.Ca./Am.Ac./B.Am./O.St. 93,9 C8:1 ; Ala ; total DMA; 27-OH-C
    508 4 En.Met/B.Am./O.St. 81,3 Fum ; Ac-Orn ; 27-OH-C ; 5a,6a-EpoxyC
    509 4 Ac.Ca./B.Am. 83,9 C5:1 ; Creatinine; SDMA ; total DMA
    510 5 Ac.Ca./S.L./B.Am./O.St. 80,6 C4:1 ; SM C24:1 ; Carnosine ; 24,25-EpoxyC ; 27-OH-C
    511 3 Ac.Ca./Am.Ac./O.St. 82,9 C8:1 ; Leu ; 27-OH-C
    512 6 En.Met/Ac.Ca./Am.Ac./B.Am. 97,3 Fum ; C5:1 ; C5-DC (C6-OH) ; Phe ; SDMA ; total DMA
    513 3 En.Met/Ac.Ca./B.Am. 80,4 Fum ; C12 ; Carnosine
    514 4 Ac.Ca./Am.Ac. 88,4 C10:2 ; C5-DC (C6-OH) ; C8:1 ; Phe
    515 4 B.Am./O.St. 83,8 Met-SO ; 24-DH-Lanosterol ; 27-OH-C ; Cholestenone
    516 4 Ac.Ca./S.L./B.Am. 81,3 C0 ; C5-DC (C6-OH) ; SM C26:0 ; Met-SO
    517 5 Ac.Ca./S.L./Am.Ac./B.Am. 82,1 C5-DC (C6-OH) ; SM (OH) C22:2 ; Pro ; Val ; SDMA
    518 4 Ac.Ca./B.Am./O.St. 82,9 C4:1 ; C5:1 ; total DMA ; 24,25-EpoxyC
    519 4 B.Am./O.St. 87,4 Ac-Orn ; total DMA ; 24,25-EpoxyC ; 27-OH-C
    520 4 Ac.Ca./B.Am./P.G. 87,5 C10:2 ; C14:1-OH ; Carnosine ; LTB4
    521 5 S.L./B.Am./O.St. 88,4 SM C24:1 ; SM C26:1 ; SM (OH) C22:1 ; total DMA ; 27-OH-C
    522 4 En.Met/Ac.Ca./S.L./B.Am. 81,2 Suc ; C8:1 ; SM C26:0 ; total DMA
    523 4 En.Met/Am.Ac./O.St. 93,5 Fum ; Tyr ; Val ; 27-OH-C
    524 5 S.L./B.Am./O.St. 91,2 SM C16:1 ; Ac-Orn ; Carnosine ; SDMA; 27-OH-C
    525 4 En.Met/Ac.Ca./S.L./B.Am. 84,1 Fum ; C5-DC (C6-OH) ; SM (OH) C14:1 ; Carnosine
    526 5 Ac.Ca./S.L./B.Am./O.St. 81,4 C10:2 ; C5:1 ; SM (OH) C14:1 ; Carnosine ; 24,25-EpoxyC
    527 4 Ac.Ca./S.L./B.Am. 83,1 C3-DC (C4-OH) ; SM C26:1 ; SM (OH) C14:1 ; Carnosine
    528 4 Ac.Ca./Am.Ac./B.Am./O.St. 87,6 C10:2 ; Thr; total DMA ; 27-OH-C
    529 4 Ac.Ca./B.Am./O.St. 95,2 C6 (C4:1-DC) ; Carnosine ; Met-SO ; 27-OH-C
    530 4 S.L./Am.Ac./B.Am./O.St. 95,1 SM (OH) C14:1 ; Tyr ; Carnosine ; 27-OH-C
    531 4 En.Met/S.L./B.Am./O.St. 91,9 Fum ; SM C24:1 ; total DMA ; 27-OH-C
    532 5 En.Met/Ac.Ca./Am.Ac./O.St. 84,5 Fum ; C5:1 ; Met; 24,25-EpoxyC ; Cholestenone
    533 3 Am.Ac./B.Am./O.St. 84,3 Asn ; Met-SO ; 27-OH-C
    534 4 Ac.Ca./S.L./B.Am. 85,6 C5-DC (C6-OH) ; SM (OH) C22:2 ; alpha-AAA ; Met-SO
    535 4 En.Met/S.L./Am.Ac./O.St. 86,5 Fum ; SM (OH) C22:2 ; Thr ; 27-OH-C
    536 5 Ac.Ca./S.L./B.Am./O.St. 89,7 C5-DC (C6-OH) ; SM C16:1 ; Carnosine ; total DMA ; 24-DH-Lanosterol
    537 4 Ac.Ca./Am.Ac./B.Am. 89,8 C5-DC (C6-OH) ; Leu ; Val ; total DMA
    538 5 S.L./Am.Ac./B.Am./O.St. 94,4 SM C16:1 ; Phe ; Carnosine ; total DMA ; 27-OH-C
    539 4 Am.Ac./O.St. 79 Met; 24,25-EpoxyC ; 27-OH-C ; 5a,6a-EpoxyC
    540 5 En.Met/Ac.Ca./B.Am./O.St. 97,6 Fum ; C5:1 ; Met-SO; total DMA ; 27-OH-C
    541 4 Ac.Ca./B.Am./O.St. 81,3 C10:2 ; Ac-Orn ; alpha-AAA ; 27-OH-C
    542 4 Ac.Ca./Am.Ac./O.St./P.G. 87,8 C0 ; Phe ; 27-OH-C ; 8-iso-PGF2a
    543 4 Am.Ac./O.St. 90,7 Phe ; 24-DH-Lanosterol ; 27-OH-C ; Cholestenone
    544 4 En.Met/Ac.Ca./B.Am. 84,4 Fum ; C2 ; SDMA ; total DMA
    545 5 En.Met/Ac.Ca./B.Am. 84,9 Fum ; C10:2 ; C5-DC (C6-OH) ; Ac-Orn ; Carnosine
    546 4 Ac.Ca./S.L./B.Am./O.St. 86,5 C8:1 ; SM (OH) C16:1 ; Carnosine; 27-OH-C
    547 4 Ac.Ca./S.L./B.Am. 84 C14:1 ; C5-DC (C6-OH); SM (OH) C22:2 ; Carnosine
    548 3 Ac.Ca./Am.Ac. 85 C10:2 ; C5-DC (C6-OH) ; Tyr
    549 5 En.Met/Ac.Ca./Am.Ac./O.St. 85,5 Lac ; C5:1-DC ; C6 (C4:1-DC) ; Phe ; 24,25-EpoxyC
    550 6 En.Met/Ac.Ca./Am.Ac./B.Am. 91,4 Pent-P ; C5:1 ; C8:1 ; Cit ; Phe ; SDMA
    551 4 En.Met/Ac.Ca./S.L./B.Am. 82,4 Fum ; C3-DC (C4-OH) ; SM (OH) C22:2 ; SDMA
    552 4 Ac.Ca./B.Am./O.St. 83,2 C5-DC (C6-OH) ; Carnosine ; total DMA ; 24-DH-Lanosterol
    553 3 Ac.Ca./Am.Ac./B.Am. 89,7 C5-DC (C6-OH) ; Lys ; total DMA
    554 4 Ac.Ca./S.L./B.Am. 89,1 C5:1 ; SM (OH) C22:2 ; SDMA ; total DMA
    555 5 Ac.Ca./S.L./B.Am. 80,8 C10:2 ; C5:1 ; C8:1 ; SM (OH) C14:1 ; Met-SO
    556 4 Ac.Ca./S.L./B.Am./O.St. 88,8 C10:2 ; SM C24:1 ; Carnosine ; 27-OH-C
    557 4 Ac.Ca./S.L./B.Am. 84,9 C10:2 ; C5:1 ; SM C16:1 ; total DMA
    558 4 En. Met/Am.Ac./B.Am./O.St. 94,7 Fum ; Ala ; total DMA ; 27-OH-C
    559 4 En.Met/S.L./B.Am./O.St. 91,4 Pent-P ; SM C26:0 ; Met-SO ; 27-OH-C
    560 4 En.Met/Ac.Ca./S.L./B.Am. 83,4 Fum ; C6 (C4:1-DC) ; SM (OH) C22:2 ; Carnosine
    561 4 Ac.Ca./S.L./B.Am./O.St. 98,3 C5:1 ; SM (OH) C22:2 ; total DMA ; 27-OH-C
    562 4 En.Met/Ac.Ca./B.Am. 93,5 Lac ; C10:2 ; C14:1-OH ; Carnosine
    563 4 En.Met/Ac.Ca./O.St. 84 Fum ; C14:1-OH ; C5:1-DC ; 24,25-EpoxyC
    564 4 En.Met/Ac.Ca./B.Am./P.G. 85,2 Fum ; C8:1 ; Carnosine ; 8-iso-PGF2a
    565 4 Ac.Ca./S.L./Am.Ac./O.St. 81,9 C5-DC (C6-OH) ; SM (OH) C14:1 ; Tyr ; Cholestenone
    566 5 En.Met/Ac.Ca./B.Am./O.St. 87 Fum ; C14:1 ; Carnosine ; 24S-OH-C ; 27-OH-C
    567 4 En.Met/Ac.Ca./Am.Ac./O.St. 80,1 Fum ; C8:1 ; Leu ; 27-OH-C
    568 4 Ac.Ca./S.L./B.Am. 89,4 C5-DC (C6-OH) ; SM (OH) C14:1 ; SM (OH) C22:2 ; Carnosine
    569 4 En.Met/S.L./B.Am. 82,3 Pent-P ; Suc ; SM C26:0 ; SDMA
    570 5 En.Met/Ac.Ca./Am.Ac./B.Am. 81,2 Fum ; C10:2 ; C6 (C4:1-DC) ; Tyr ; SDMA
    571 6 Ac.Ca./B.Am./O.St. 90,9 C5:1 ; C5-DC (C6-OH) ; Ac-Orn ; alpha-AAA ; total DMA ; 24,25-EpoxyC
    572 5 Ac.Ca./Am.Ac./B.Am. 80,6 C4:1 ; C5-DC (C6-OH) ; C8:1 ; Ala ; total DMA
    573 5 En.Met/Ac.Ca./O.St. 80,5 Fum ; C14:1 ; C5:1 ; 24-DH-Lanosterol ; 3b,5a,6b-THC
    574 4 En. Met/Ac.Ca./B.Am./O.St. 87,2 Fum ; C5:1 ; Met-SO ; 24,25-EpoxyC
    575 5 Ac.Ca./Am.Ac./B.Am./O.St. 84,6 C5:1 ; Glu ; SDMA ; 24-DH-Lanosterol ; Cholestenone
    576 4 En.Met/Ac.Ca./S.L./B.Am. 86,1 Pent-P ; C3-DC (C4-OH) ; SM (OH) C22:2 ; Carnosine
    577 4 Ac.Ca./Am.Ac./B.Am./O.St. 90 C10:2 ; Pro ; total DMA ; 27-OH-C
    578 4 En.Met/Ac.Ca./S.L./B.Am. 85,5 Suc ; C5-DC (C6-OH) ; SM C26:0 ; total DMA
    579 5 En.Met/Ac.Ca./B.Am. 91,3 Fum ; Pent-P ; C6 (C4:1-DC) ; Ac-Orn ; total DMA
    580 4 En.Met/S.L./B.Am./O.St. 84,9 Fum ; SM C16:1 ; Ac-Orn ; 27-OH-C
    581 4 En.Met/Ac.Ca./Am.Ac./O.St. 80,2 Fum ; C5-DC (C6-OH) ; Phe ; 24,25-EpoxyC
    582 4 Ac.Ca./S.L./B.Am. 88 C5-DC (C6-OH) ; SM C16:0; SM (OH) C16:1 ; Carnosine
    583 4 En.Met/Ac.Ca./B.Am./O.St. 88,1 Lac ; C14:1-OH ; Carnosine ; 27-OH-C
    584 4 Ac.Ca./S.L./B.Am./O.St. 84,7 C5:1 ; SM (OH) C14:1 ; SDMA ; 27-OH-C
    585 4 Ac.Ca./S.L./B.Am. 91,4 C5-DC (C6-OH) ; SM (OH) C22:2 ; Carnosine ; SDMA
    586 6 Ac.Ca./S.L./Am.Ac./O.St. 96,2 C10:2 ; C5:1 ; C8:1 ; SM C24:1 ; Phe ; 24,25-EpoxyC
    587 4 Ac.Ca./S.L./B.Am./O.St. 79,8 C5:1 ; SM C16:0 ; Carnosine ; Cholestenone
    588 4 En.Met/Ac.Ca./B.Am. 86,4 Fum ; C14:1 ; Ac-Orn ; Carnosine
    589 4 Ac.Ca./S.L./Am.Ac./B.Am. 82,6 C5-DC (C6-OH) ; SM (OH) C14:1 ; Tyr ; alpha-AAA
    590 5 Ac.Ca./B.Am./O.St. 95,3 C10:2 ; C14:1 ; Carnosine; Met-SO ; 27-OH-C
    591 4 Ac.Ca./B.Am./O.St. 80,8 C5:1 ; Met-SO ; total DMA ; 24,25-EpoxyC
    592 4 Ac.Ca./Am.Ac./O.St. 91,2 C10:2 ; C8:1 ; Val ; 27-OH-C
    593 5 Ac.Ca./S.L./Am.Ac. 90,5 C10:2 ; C5:1 ; C8:1 ; SM C16:0 ; Phe
    594 5 Ac.Ca./S.L./O.St. 80 C5:1 ; SM C16:1 ; SM C24:1 ; 27-OH-C ; Cholestenone
    595 5 Ac.Ca./B.Am./O.St. 84,8 C5:1-DC ; Ac-Orn ; alpha-AAA ; SDMA ; 27-OH-C
    596 4 En.Met/Ac.Ca./B.Am. 90,6 Fum ; C5-OH (C3-DC-M) ; Carnosine ; total DMA
    597 4 En.Met/B.Am./O.St. 87,1 Fum ; Carnosine ; SDMA ; 27-OH-C
    598 5 En.Met/Ac.Ca./S.L./B.Am. 87,2 Fum ; C5:1 ; C8:1 ; SM (OH) C14:1 ; Carnosine
    599 4 S.L./B.Am./O.St. 94,3 SM (OH) C14:1 ; Ac-Orn ; Carnosine ; 27-OH-C
    600 5 S.L./Am.Ac./B.Am./O.St. 90,7 SM (OH) C14:1 ; SM (OH) C22:2 ; Thr ; total DMA ; 27-OH-C
    601 4 Ac.Ca./Am.Ac./B.Am. 79,1 C5-DC (C6-OH) ; Tyr ; Val ; SDMA
    602 4 En.Met/B.Am./O.St./P.G. 80,6 Fum ; Carnosine ; 27-OH-C ; 8-iso-PGF2a
    603 4 En.Met/B.Am. 85,8 Fum ; Pent-P ; SDMA ; total DMA
    604 5 Ac.Ca./S.L./B.Am./O.St. 79 C10:2 ; C5:1 ; SM C16:0 ; Carnosine ; 24,25-EpoxyC
    605 5 Ac.Ca./S.L./B.Am. 82,3 C0 ; SM (OH) C14:1 ; SM (OH) C22:2 ; Carnosine ; total DMA
    606 4 En.Met/Ac.Ca. 82,7 Fum; Pent-P ; Suc ; C14:1-OH
    607 4 En.Met/B.Am./O.St. 86,3 Fum ; Ac-Orn ; 27-OH-C ; Cholestenone
    608 5 B.Am./O.St. 85 Carnosine ; SDMA ; 24-DH-Lanosterol ; 27-OH-C ; Cholestenone
    609 4 En.Met/S.L./B.Am./O.St. 80,9 Fum ; SM C16:0 ; Carnosine ; 27-OH-C
    610 4 Ac.Ca./S.L./Am.Ac. 84,8 C5-DC (C6-OH) ; SM (OH) C22:2 ; Lys ; Tyr
    611 5 Ac.Ca./Am.Ac./B.Am./O.St. 91,9 C5:1 ; Met; total DMA ; 24,25-EpoxyC ; 27-OH-C
    612 4 Ac.Ca./Am.Ac./O.St. 83,2 C5-DC (C6-OH) ; C8:1 ; Tyr ; 24,25-EpoxyC
    613 5 En.Met/Ac.Ca./S.L./B.Am. 89,5 Pent-P ; C5:1 ; SM (OH) C14:1 ; alpha-AAA ; SDMA
    614 4 En.Met/Ac.Ca./Am.Ac./O.St. 85,6 Fum ; C8:1 ; Phe ; 27-OH-C
    615 4 En.Met/Ac.Ca./B.Am. 89,9 Fum ; C5-DC (C6-OH) ; alpha-AAA ; Met-SO
    616 6 En.Met/S.L./Am.Ac./B.Am./O.St. 84,8 Pent-P ; SM (OH) C14:1 ; Cit ; Phe ; Ac-Orn; 27-OH-C
    617 4 Ac.Ca./S.L./B.Am./O.St. 82,8 C5:1 ; SM C16:1 ; SDMA ; 27-OH-C
    618 4 Ac.Ca./S.L./B.Am. 81,1 C10:2 ; C8:1 ; SM (OH) C14:1 ; Carnosine
    619 4 S.L./B.Am./O.St. 83,9 SM C16:0 ; alpha-AAA; Carnosine ; 27-OH-C
    620 4 En.Met/B.Am./O.St. 93,1 Fum ; OAA ; total DMA ; 27-OH-C
    621 4 En.Met/Ac.Ca./B.Am. 90,2 Fum ; C4:1 ; C5-DC (C6-OH) ; Met-SO
    622 4 En.Met/S.L./B.Am./O.St. 95,5 Fum ; SM C16:1 ; Met-SO ; 27-OH-C
    623 5 Ac.Ca./S.L./B.Am./O.St. 85,6 C8:1 ; SM C26:0 ; Ac-Orn ; Carnosine ; 27-OH-C
    624 5 Ac.Ca./Am.Ac./B.Am./O.St. 84,5 C8:1 ; Cit ; Ac-Orn ; Carnosine ; 27-OH-C
    625 5 En.Met/Ac.Ca./B.Am. 80,6 Fum ; Pent-P ; Suc ; C6 (C4:1-DC); Ac-Orn
    626 4 Ac.Ca./B.Am./O.St. 94,4 C5-DC (C6-OH) ; alpha-AAA ; Met-SO ; 27-OH-C
    627 4 Ac.Ca./Am.Ac./B.Am. 93,3 C5-DC (C6-OH) ; C8:1 ; Pro ; total DMA
    628 4 Ac.Ca./S.L./B.Am./O.St. 82,4 C0 ; SM (OH) C22:2 ; total DMA ; 3b,5a,6b-THC
    629 4 En.Met/Ac.Ca./B.Am./O.St. 95,5 Fum ; C14:1-OH ; Met-SO ; 27-OH-C
    630 5 En.Met/Ac.Ca./Am.Ac./B.Am. 94,7 Hex-P ; C5-DC (C6-OH) ; Leu ; Pro ; total DMA
    631 4 En.Met/Ac.Ca./O.St. 82 Fum ; Suc ; C14:2-OH ; 27-OH-C
    632 4 Ac.Ca./S.L./Am.Ac./B.Am. 83,4 C5-DC (C6-OH) ; SM C16:1 ; Tyr; alpha-AAA
    633 4 Ac.Ca./S.L./Am.Ac. 82,3 C10:2 ; C5-DC (C6-OH) ; SM (OH) C22:2 ; Thr
    634 4 Ac.Ca./B.Am. 88,1 C10:2 ; C6 (C4:1-DC) ; C8:1 ; Carnosine
    635 5 Ac.Ca./S.L./B.Am./O.St. 91 C10:2 ; SM (OH) C14:1 ; Met-SO ; 27-OH-C ; 5a,6a-EpoxyC
    636 5 En.Met/Ac.Ca./B.Am./O.St. 88,9 Fum ; C14:1-OH ; C5:1 ; Ac-Orn ; 3b,5a,6b-THC
    637 4 En.Met/Am.Ac./B.Am./O.St. 94,3 Fum ; Phe ; Met-SO ; 27-OH-C
    638 3 En.Met/B.Am./O.St. 83,6 Fum ; Met-SO ; 24,25-EpoxyC
    639 4 En.Met/Am.Ac./B.Am./O.St. 95,6 Fum ; Val ; Met-SO ; 27-OH-C
    640 3 S.L./B.Am./O.St. 90,4 SM C16:1 ; Met-SO ; 27-OH-C
    641 5 En.Met/Ac.Ca./S.L./B.Am./O.St. 83,6 Fum ; C5:1-DC ; SM (OH) C14:1 ; Carnosine; 27-OH-C
    642 4 Ac.Ca./Am.Ac./O.St./P.G. 84,6 C14:1 ; Phe ; 27-OH-C ; 8-iso-PGF2a
    643 4 Am.Ac./O.St./P.G. 85,9 Thr; 27-OH-C ; 8-iso-PGF2a ; LTB4
    644 4 En.Met/Ac.Ca./S.L./B.Am. 86,8 Fum ; C5-DC (C6-OH) ; SM (OH) C22:2 ; Met-SO
    645 4 Ac.Ca./B.Am./O.St. 84,5 C5:1 ; Ac-Orn ; total DMA ; 24,25-EpoxyC
    646 4 En. Met/Am.Ac./B.Am./O.St. 94,3 Fum ; Met; total DMA ; 27-OH-C
    647 5 En.Met/Ac.Ca./B.Am. 82,4 Suc ; C5-DC (C6-OH) ; alpha-AAA ; Met-SO ; Spermidine
    648 4 Am.Ac./O.St. 94 Tyr ; 24-DH-Lanosterol ; 27-OH-C ; Cholestenone
    649 5 En.Met/Ac.Ca./B.Am. 87,9 Fum ; C5 ; Met-SO ; SDMA ; total DMA
    650 6 En.Met/Ac.Ca./B.Am./P.G. 80,9 Lac ; C10:2 ; C5-DC (C6-OH) ; C8:1 ; total DMA ; LTB4
    651 3 En.Met/Am.Ac./O.St. 90,1 Fum ; Asp; 27-OH-C
    652 6 Ac.Ca./S.L./B.Am./O.St. 85,7 C5-DC (C6-OH) ; C8:1 ; SM (OH) C22:2 ; Ac-Orn ; Carnosine ; 24,25-EpoxyC
    653 4 En.Met/Ac.Ca./B.Am./O.St. 95,4 Fum ; C5:1 ; total DMA; 27-OH-C
    654 5 En.Met/Ac.Ca./S.L./B.Am. 86,6 Pent-P ; C4 ; SM C24:1 ; SM (OH) C22:2 ; Carnosine
    655 5 Ac.Ca./Am.Ac./B.Am. 97 C10:2 ; C5-DC (C6-OH) ; C6 (C4:1-DC) ; Tyr ; Carnosine
    656 5 En.Met/B.Am./O.St. 85,3 Fum ; Suc ; Met-SO; SDMA ; 24,25-EpoxyC
    657 4 En.Met/Ac.Ca./S.L./B.Am. 87,5 Fum ; C3-DC (C4-OH) ; SM (OH) C22:2 ; Carnosine
    658 4 S.L./B.Am./O.St. 89 SM (OH) C14:1 ; Carnosine ; Met-SO ; 27-OH-C
    659 5 En.Met/Ac.Ca./B.Am./O.St. 89,3 Fum ; C4:1 ; C5:1 ; Met-SO ; 24,25-EpoxyC
    660 3 S.L./B.Am./O.St. 85 SM (OH) C16:1 ; Carnosine ; 27-OH-C
    661 6 Ac.Ca./B.Am./O.St. 83,9 C0; C10:2 ; C14:2-OH ; Carnosine ; Met-SO ; 24,25-EpoxyC
    662 6 En.Met/Ac.Ca./Am.Ac./B.Am./O.St. 96,4 Fum ; C5:1 ; His ; SDMA ; total DMA ; 27-OH-C
    663 5 En.Met/Am.Ac./B.Am./O.St./P.G. 90,1 Fum ; Phe ; Carnosine ; 27-OH-C ; DHA
    664 4 En.Met/Ac.Ca./B.Am./O.St. 95,5 Fum ; C3-DC (C4-OH) ; Met-SO ; 27-OH-C
    665 6 En.Met/Ac.Ca./Am.Ac./B.Am./O.St. 87,7 Suc ; C5-DC (C6-OH) ; Tyr ; Ac-Orn ; alpha-AAA ; 24,25-EpoxyC
    666 4 Ac.Ca./B.Am./O.St. 86,6 C14:1 ; C5:1 ; total DMA ; 3b,5a,6b-THC
    667 5 Ac.Ca./S.L./B.Am. 81,1 C10:2 ; C5:1 ; SM C16:0 ; SM C16:1 ; Carnosine
    668 4 Ac.Ca./Am.Ac./B.Am. 83,5 C5-DC (C6-OH); Tyr ; SDMA ; total DMA
    669 4 Ac.Ca./Am.Ac./B.Am. 79,9 C5-DC (C6-OH) ; Leu ; Lys ; SDMA
    670 4 En.Met/Ac.Ca./B.Am./O.St. 94,3 Fum ; C6 (C4:1-DC) ; Met-SO ; 27-OH-C
    671 5 En.Met/Ac.Ca./Am.Ac./B.Am. 94,7 Fum ; C10:2 ; C5-DC (C6-OH) ; Phe ; SDMA
    672 3 Ac.Ca./S.L./Am.Ac. 87 C5-DC (C6-OH) ; SM (OH) C22:2 ; Tyr
    673 4 Ac.Ca./S.L./B.Am. 79,1 C6 (C4:1-DC) ; SM (OH) C22:2 ; Carnosine ; total DMA
    674 4 En.Met/Ac.Ca./B.Am. 89,5 Fum ; C14:1-OH ; C6 (C4:1-DC); Met-SO
    675 4 Ac.Ca./S.L./Am.Ac./O.St. 91,3 C10:2 ; SM (OH) C22:2 ; Thr ; 27-OH-C
    676 4 S.L./B.Am./O.St. 86,1 SM C16:1 ; Carnosine; SDMA ; 27-OH-C
    677 5 En.Met/Ac.Ca./B.Am. 92,7 Fum ; C10:2 ; C6 (C4:1-DC) ; Ac-Orn ; Carnosine
    678 5 Ac.Ca./S.L./B.Am. 80,5 C3-DC (C4-OH) ; SM C16:1 ; SM (OH) C14:1 ; Carnosine ; total DMA
    679 4 En.Met/B.Am./O.St. 96,3 Fum ; Met-SO; 27-OH-C ; Cholestenone
    680 4 Ac.Ca./Am.Ac./B.Am./O.St. 87 C10:2 ; Lys ; Ac-Orn ; 27-OH-C
    681 4 En.Met/Ac.Ca./B.Am. 89,6 Fum ; C6 (C4:1-DC); Carnosine ; total DMA
    682 5 Ac.Ca./S.L./Am.Ac./B.Am./O.St. 94,1 C5:1 ; SM (OH) C14:1 ; Phe ; SDMA ; 27-OH-C
    683 4 Ac.Ca./B.Am./O.St. 82,7 C5:1 ; total DMA ; Cholestenone ; 3b,5a,6b-THC
    684 4 En.Met/B.Am./O.St. 86,1 Fum ; SDMA ; Spermidine ; 27-OH-C
    685 5 En.Met/B.Am./O.St. 96,6 Fum ; Met-SO ; SDMA ; 27-OH-C ; Cholestenone
    686 3 En.Met/Am.Ac./O.St. 80,6 Fum ; Asn ; 27-OH-C
    687 5 Ac.Ca./S.L./Am.Ac. 79,1 C10:2 ; C5-DC (C6-OH) ; C8:1 ; SM (OH) C22:2 ; Val
    688 5 En.Met/Ac.Ca./B.Am. 92,4 Fum ; C4:1 ; C5:1 ; Met-SO ; SDMA
    689 5 Ac.Ca./S.L./B.Am. 80,4 C0 ; C8:1 ; SM (OH) C14:1 ; Carnosine ; total DMA
    690 4 En.Met/Ac.Ca./B.Am. 94,7 Fum ; C5-DC (C6-OH); Met-SO ; SDMA
    691 3 Ac.Ca./B.Am./O.St. 83,1 C5:1 ; total DMA; 3b,5a,6b-THC
    692 4 En.Met/Ac.Ca./Am.Ac. 87,4 Fum ; C10:2 ; C6 (C4:1-DC) ; Phe
    693 4 Ac.Ca./S.L./B.Am. 83,8 C14:2-OH ; C5-DC (C6-OH) ; SM C26:0 ; total DMA
    694 4 En.Met/Ac.Ca./B.Am./O.St. 80 Fum ; C10 ; Ac-Orn ; 27-OH-C
    695 4 Ac.Ca./B.Am./O.St. 83,3 C6 (C4:1-DC) ; Ac-Orn ; Carnosine ; 24,25-EpoxyC
    696 4 S.L./Am.Ac./O.St. 90,3 SM C16:1 ; Phe ; 27-OH-C ; Cholestenone
    697 4 En.Met/Ac.Ca./S.L./B.Am. 82,5 Fum ; C2 ; SM (OH) C22:2 ; Carnosine
    698 5 Ac.Ca./S.L./B.Am./O.St. 89,6 C5-DC (C6-OH) ; SM (OH) C22:2 ; SDMA ; total DMA ; 3b,5a,6b-THC
    699 3 S.L./O.St. 80,1 SM C26:1 ; SM (OH) C22:2 ; 27-OH-C
    700 4 En.Met/Ac.Ca./B.Am./O.St. 86,1 Fum ; C16:2 ; SDMA ; 27-OH-C
    701 5 Ac.Ca./Am.Ac./B.Am./O.St. 83,5 C5:1 ; Cit ; Ac-Orn ; SDMA ; 3b,5a,6b-THC
    702 5 En.Met/Ac.Ca./Am.Ac./O.St. 93,4 Fum ; C5:1 ; Met; 24,25-EpoxyC ; 27-OH-C
    703 4 Ac.Ca./S.L./B.Am. 80 C5-DC (C6-OH) ; SM C24:1 ; Ac-Orn ; alpha-AAA
    704 4 Ac.Ca./B.Am./P.G. 87,5 C6 (C4:1-DC); Carnosine ; 8-iso-PGF2a ; LTB4
    705 4 Ac.Ca./S.L./Am.Ac./B.Am. 86,4 C5-DC (C6-OH) ; SM (OH) C14:1 ; Lys ; total DMA
    706 4 Ac.Ca./S.L./B.Am. 88,3 C5-DC (C6-OH) ; SM C16:1 ; alpha-AAA ; Met-SO
    707 5 Ac.Ca./B.Am./P.G. 85,8 C10:2 ; C5:1 ; C8:1 ; total DMA / LTB4
    708 4 En.Met/Ac.Ca./S.L./B.Am. 83,6 Pent-P ; C6 (C4:1-DC) ; SM (OH) C22:2 ; Carnosine
    709 4 En.Met/Ac.Ca./B.Am. 86 Fum ; C6 (C4:1-DC); C8:1 ; Carnosine
    710 4 Ac.Ca./B.Am./O.St. 81,4 C5:1 ; Met-SO ; SDMA ; 24,25-EpoxyC
    711 4 En.Met/Am.Ac./B.Am./O.St. 82,9 Fum ; Leu ; Carnosine ; 27-OH-C
    712 4 Ac.Ca./B.Am. 87,6 C10:2 ; C5-DC (C6-OH) ; alpha-AAA ; Met-SO
    713 4 S.L./Am.Ac./O.St. 81,9 SM (OH) C22:2 ; Lys ; Val ; 27-OH-C
    714 4 En.Met/Ac.Ca./B.Am. 90,3 Fum ; C5-DC (C6-OH) ; C8:1 ; Met-SO
    715 6 Ac.Ca./S.L./Am.Ac./B.Am. 80,5 C10:2 ; C4:1 ; C5:1 ; SM (OH) C14:1 ; Phe ; alpha-AAA
    716 5 Ac.Ca./S.L./Am.Ac./B.Am./O.St. 90,7 C5:1 ; SM C24:1 ; Cit ; SDMA ; 5a,6a-EpoxyC
    717 4 En.Met/S.L./Am.Ac./B.Am. 79,3 Fum ; SM (OH) C22:2 ; Arg ; total DMA
    Table 11: Combinations formed with a lead metabolite that correlate with damage of hippocampus
    No. Npar Accuracy Lead metabolite Additional metabolites
    1 3 91,5 C10:2 Ac-Orn;Fum
    2 3 86,6 C10:2 Lac;Phe
    3 4 91,3 C10:2 8-iso-PGF2a;Ac-Orn;Fum
    4 4 89,7 C10:2 Ac-Orn;Lac;Pent-P
    5 4 89,4 C10:2 Ac-Orn;C16:2;Fum
    6 4 89,1 C10:2 Ac-Orn;Carnosine;Lac
    7 4 88,7 C10:2 C5:1-DC;Carnosine;Lac
    8 3 85,1 SM C24:1 C16:2;C5:1
    9 4 92,8 SM C24:1 C5:1;Carnosine;Lac
    10 4 88,1 SM C24:1 Ac-Orn;C16:2;C5:1
    11 4 86,2 SM C24:1 Ac-Orn;C16:2;Lac
    12 4 85,8 SM C24:1 Ac-Orn;C16:2;Pent-P
    13 5 87,6 SM C24:1 5a,6a-EpoxyC;Ac-Orn;C5:1;Lac
    14 3 94 C5:1-DC Ac-Orn;Fum
    15 4 91,7 C5:1-DC 24S-OH-C;25-OH-C;alpha-AAA
    16 4 89,5 C5:1-DC Creatinine;Fum;total DMA
    17 4 88,7 C5:1-DC C10:2;Carnosine;Lac
    18 4 87,2 C5:1-DC Fum;Lac;total DMA
    19 4 87 C5:1-DC Carnosine;Fum;SM (OH) C22:2
    20 4 86,7 C5:1-DC alpha-AAA;Carnosine;Suc
    21 4 86,4 C5:1-DC Fum;Lac;Pent-P
    22 3 93,4 Suc Carnosine;Lac
    23 4 95 Suc Carnosine;Lac;Pent-P
    24 4 86,7 Suc alpha-AAA;C5:1-DC;Carnosine
    25 4 86,4 Suc Fum; Lac; Met-SO
    Table 12: Combinations formed with a lead metabolite that correlate with damage of basal ganglia
    No Npar Accuracy Lead metabolite Additional metabolites
    1 3 91,9 Met-SO Gln;Lys
    2 4 92,9 Met-SO Gln;Lac;SM C24:0
    3 4 92,2 Met-SO Gln;Orn;SM (OH) C14:1
    4 4 91,8 Met-SO Gln;Orn;SM (OH) C22:2
    5 4 91,5 Met-SO Gln;Pro;SM C24:0
    6 4 91,4 Met-SO Kynurenine;SM (OH) C14:1;SM (OH) C22:1
    7 4 91,3 Met-SO Gln;Lys;SM (OH) C22:1
    8 4 91,1 Met-SO Cholestenone;Creatinine;Trp
    9 4 91,1 Met-SO Gln;Pro;SM C16:1
    10 4 90,5 Met-SO C6:1;SM (OH) C22:1;Trp
    11 4 90,5 Met-SO Gln;Pro;SM (OH) C14:1
    12 4 90,1 Met-SO His;Orn;SMC24:0
    13 5 92,8 Met-SO Pro;SM C16:1;SM C24:0;Trp
    14 5 91,4 Met-SO Gln;Orn;Pro;SM C16:1
    15 5 91,1 Met-SO C6:1;Gln;Lac;SM C16:0
    16 5 90,9 Met-SO Orn;SM C24:0;SM (OH) C22:1;SM (OH) C22:2
    17 5 90,6 Met-SO Pro;SM C16:1;SM C24:1;Trp
    18 5 90,5 Met-SO alpha-KGA;His;Kynurenine;SM C16:1
    19 5 90,1 Met-SO Gln;His;Orn;SM (OH) C22:2
    20 5 90,1 Met-SO Cholestenone;SM C18:0;SM (OH) C22:1;Trp
    21 5 90,1 Met-SO Gln;Lac;SM C16:1;SM (OH) C14:1
    22 6 96,5 Met-SO 24-DH-Lanosterol;Arg;Creatinine;SM C16:1;Trp
    23 6 91,6 Met-SO Gly;LTB4;SM C16:1;SM (OH) C22:1 ;SM (OH) C22:2
    24 6 90,5 Met-SO Cholestenone;Gln;Lys;SM C24:0;SM (OH) C22:1
    25 6 90,4 Met-SO 8-iso-PGF2a;Pro;Serotonin;SM (OH) C22:1;Trp
    26 6 90,4 Met-SO Kynurenine;LTB4;SM C16:0;SM (OH) C14:1;SM (OH) C22:1
    27 3 92,5 SM (OH) C14:1 Kynurenine;Tyr
    28 3 90,9 SM (OH) C14:1 C5:1-DC;C6:1
    29 4 97,2 SM (OH) C14:1 20a-OH-C;SM (OH) C22:1;Tyr
    30 4 95,6 SM (OH) C14:1 Kynurenine;SM (OH) C22:2;Tyr
    31 4 95,2 SM (OH) C14:1 Pro;SM C16:1;TXB2
    32 4 94,7 SM (OH) C14:1 Pro;SM C16:0;TXB2
    33 4 93,9 SM (OH) C14:1 20a-OH-C;SM (OH) C22:2;Tyr
    34 4 93,1 SM (OH) C14:1 Gln;Pro;TXB2
    35 4 92,7 SM (OH) C14:1 His;Kynurenine;Tyr
    36 4 92,3 SM (OH) C14:1 C5:1-DC;Pro;SM C16:1
    37 4 92,3 SM (OH) C14:1 20a-OH-C;Arg;SM (OH) C22:2
    38 4 92,2 SM (OH) C14:1 Gln;Met-SO;Orn
    39 4 92,1 SM (OH) C14:1 Kynurenine;Leu;Met
    40 4 92 SM (OH) C14:1 Kynurenine;Leu;Tyr
    41 4 91,5 SM (OH) C14:1 Met;Pro;Trp
    42 4 91,4 SM (OH) C14:1 Kynurenine;Met-SO;SM (OH) C22:1
    43 4 91,3 SM (OH) C14:1 Pro;SM C26:1;TXB2
    44 4 91,2 SM (OH) C14:1 Lys;SM (OH) C16:1;TXB2
    45 4 90,9 SM (OH) C14:1 25-OH-C;C5:1-DC;Histamine
    46 4 90,8 SM (OH) C14:1 Gln;Lac;Met
    47 4 90,7 SM (OH) C14:1 C5:1-DC;C6:1;SM C16:0
    48 4 90,6 SM (OH) C14:1 Kynurenine;SM C16:1;Tyr
    49 4 90,5 SM (OH) C14:1 Gln;Met-SO;Pro
    50 4 90,5 SM (OH) C14:1 Ac-Orn;Pro;SM C16:1
    51 4 90,4 SM (OH) C14:1 C5:1-DC;SM (OH) C22:1;Tyr
    52 4 90,3 SM (OH) C14:1 C5:1-DC;SM C16:1;Tyr
    53 4 90,2 SM (OH) C14:1 C5:1-DC;Histamine;SM C16:0
    54 4 90,2 SM (OH) C14:1 alpha-KGA;SM (OH) C22:2;TXB2
    55 4 90,1 SM (OH) C14:1 20a-OH-C;Pro;SM C16:1
    56 4 90 SM (OH) C14:1 SM C20:2;SM (OH) C22:1;Tyr
    57 5 94,7 SM (OH) C14:1 Kynurenine;Met;SM (OH) C22:1;Tyr
    58 5 94,2 SM (OH) C14:1 Arg;SM C24:0;SM (OH) C22:2;TXB2
    59 5 94,2 SM (OH) C14:1 Kynurenine;LTB4;SM (OH) C16:1;Tyr
    60 5 93,7 SM (OH) C14:1 Ala;C5:1-DC;SM C16:0;SM C16:1
    61 5 93 SM (OH) C14:1 20a-OH-C;Arg;Leu;SM C16:1
    62 5 92,6 SM (OH) C14:1 Kynurenine;SM (OH) C16:1;SM (OH) C22:1 ;Tyr
    63 5 92,5 SM (OH) C14:1 Lys;SM (OH) C22:1;SM (OH) C22:2;TXB2
    64 5 92,4 SM (OH) C14:1 His;Orn;SM C24:0;TXB2
    65 5 91,6 SM (OH) C14:1 C5:1-DC;C6:1;Orn;SM C16:0
    66 5 91,5 SM (OH) C14:1 20a-OH-C;C6:1;Gln;Tyr
    67 5 91,3 SM (OH) C14:1 Ala;SM C16:1;SM C18:1;TXB2
    68 5 90,9 SM (OH) C14:1 Kynurenine;SM C18:1;SM (OH) C16:1;Tyr
    69 5 90,8 SM (OH) C14:1 25-OH-C;C5:1-DC;Histamine;Orn
    70 5 90,4 SM (OH) C14:1 Ac-Orn;Cholestenone;Pro;SM C16:1
    71 5 90,4 SM (OH) C14:1 Ac-Orn;Gln;Pro;SM (OH) C22:2
    72 5 90,4 SM (OH) C14:1 24-DH-Lanosterol;Ac-Orn;Orn;Trp
    73 5 90,2 SM (OH) C14:1 8-iso-PGF2a;Gln;Met;Orn
    74 5 90,2 SM (OH) C14:1 Gly;Pro;SM C16:0;SM C24:1
    75 5 90,1 SM (OH) C14:1 Gln;Lac;Met-SO;SM C16:1
    76 5 90 SM (OH) C14:1 Kynurenine;LTB4;Phe;SM (OH) C22:2
    77 5 90 SM (OH) C14:1 Ac-Orn;Pro;SM C24:1 ;Trp
    78 5 90 SM (OH) C14:1 Orn;Ser;SM C24:1;SM (OH) C22:2
    79 6 96,6 SM (OH) C14:1 Lys;SM C18:1;SM (OH) C22:1;TXB2;Tyr
    80 6 93,5 SM (OH) C14:1 20a-OH-C;C14:1;His;Pro;SM (OH) C22:2
    81 6 93,4 SM (OH) C14:1 25-OH-C;Arg;Histamine;SM (OH) C22:2;TXB2
    82 6 93 SM (OH) C14:1 24-DH-Lanosterol;Ac-Orn;C6:1;SM C18:1;Trp
    83 6 92,7 SM (OH) C14:1 20a-OH-C;His;SM C24:0;SM (OH) C16:1;Tyr
    84 6 91 SM (OH) C14:1 C5:1-DC;Cholestenone;Histamine;Orn;SM (OH) C22:1
    85 6 90,4 SM (OH) C14:1 Kynurenine;LTB4;Met-SO;SM C16:O;SM (OH) C22:1
    86 6 90 SM (OH) C14:1 25-OH-C;Ala;Met;Orn;SM C24:0
    87 7 92,9 SM (OH) C14:1 Ac-Orn;Ala;C6:1;Gln;Orn;SM C16:1
    88 4 96,8 alpha-KGA C14:1;Pro;TXB2
    89 4 95,4 95,4 alpha-KGA Lys;SM (OH) C22:2;TXB2
    90 4 95,1 alpha-KGA 20a-OH-C;SM C16:1;Tyr
    91 4 91 alpha-KGA 22R-OH-C;Pro;SM C16:1
    92 4 90,2 alpha-KGA SM (OH) C14:1;SM (OH) C22:2;TXB2
    93 4 90,1 alpha-KGA 20a-OH-C;SM C16:1;SM (OH) C22:2
    94 5 96 alpha-KGA 20a-OH-C;Gln;SM (OH) C22:2;Tyr
    95 5 95,8 alpha-KGA His;Orn;SM (OH) C22:2;TXB2
    96 5 92,6 alpha-KGA Pro;SM C16:0;SM (OH) C22:2;TXB2
    97 5 90,5 alpha-KGA Kynurenine;SM C24:1;SM (OH) C22:2;Tyr
    98 5 90,5 alpha-KGA His;Kynurenine;Met-SO;SM C16:1
    99 5 90,2 alpha-KGA Arg;C10:2;Gln;Met
    100 5 90,2 alpha-KGA 24-DH-Lanosterol;Pro;SM C24:1 ;Trp
    101 6 92,5 alpha-KGA 20a-OH-C;His;SM C16:0;SM C24:0;Tyr
    102 6 91,1 alpha-KGA Ac-Orn;Arg;Cholestenone;LTB4;Trp
    103 4 91,7 Cholestenone Fum;Met;Trp
    104 4 91,5 Cholestenone Creatinine;SM C16:1;Tyr
    105 4 91,1 Cholestenone Creatinine;Met-SO;Trp
    106 4 90,3 Cholestenone Met;SM (OH) C22:2;Trp
    107 4 90,1 Cholestenone Ala;SM C24:1 ;SM (OH) C22:2
    108 5 92,1 Cholestenone Arg;Pro;SM C16:1;Suc
    109 5 92,1 Cholestenone C5:1-DC;Gln;Lys;SM C16:1
    110 5 91,1 Cholestenone 24-DH-Lanosterol;C5:1-DC;Gln;Lys
    111 5 90,4 Cholestenone Ac-Orn;Pro;SM C16:1;SM (OH) C14:1
    112 5 90,3 Cholestenone Gly;Pro;SM C16:0;SM (OH) C22:2
    113 5 90,2 Cholestenone C5:1-DC;Orn;SM C24:0;SM (OH) C22:2
    114 5 90,1 Cholestenone Met-SO;SM C18:0;SM (OH) C22:1;Trp
    115 6 91,1 Cholestenone Ac-Orn;alpha-KGA;Arg;LTB4;Trp
    116 6 91 Cholestenone C5:1-DC;Histamine;Orn;SM (OH) C14:1;SM (OH) C22:1
    117 6 90,5 Cholestenone Gln;Lys;Met-SO;SM C24:0;SM (OH) C22:1
    118 3 93,3 SM C16:1 C5:1-DC;C6:1
    119 4 95,6 SM C16:1 Pro;SM (OH) C22:1;TXB2
    120 4 95,2 SM C16:1 Pro;SM (OH) C14:1;TXB2
    121 4 95,1 SM C16:1 20a-OH-C;alpha-KGA;Tyr
    122 4 94,6 SM C16:1 20a-OH-C;Pro;SM (OH) C22:2
    123 4 92,3 SM C16:1 C5:1-DC;Pro;SM (OH) C14:1
    124 4 92,2 SM C16:1 Gly;SM C18:1;SM (OH) C22:2
    125 4 91,8 SM C16:1 Kynurenine;SM C24:1;Tyr
    126 4 91,8 SM C16:1 C5:1-DC;Pro;SM C16:0
    127 4 91,6 SM C16:1 C5:1-DC;Orn;SM C16:0
    128 4 91,5 SM C16:1 His;Pro;TXB2
    129 4 91,5 SM C16:1 Cholestenone;Creatinine;Tyr
    130 4 91,4 SM C16:1 C5:1-DC;C6:1;Pro
    131 4 91,3 SM C16:1 Gln;Lac;Met
    132 4 91,2 SM C16:1 20a-OH-C;Leu;SM (OH) C22:2
    133 4 91,2 SM C16:1 Kynurenine;Phe;SM (OH) C22:2
    134 4 91,1 SM C16:1 Gln;Met-SO;Pro
    135 4 91 SM C16:1 Met;Pro;Trp
    136 4 91 SM C16:1 22R-OH-C;alpha-KGA;Pro
    137 4 91 SM C16:1 Kynurenine;SM C18:1;Tyr
    138 4 90,9 SM C16:1 Kynurenine;Leu;Met
    139 4 90,7 SM C16:1 C5:1-DC;C6:1;SM C24:0
    140 4 90,6 SM C16:1 20a-OH-C;SM (OH) C24:1;Tyr
    141 4 90,6 SM C16:1 Kynurenine;SM (OH) C14:1;Tyr
    142 4 90,5 SM C16:1 Kynurenine;SM (OH) C22:1;Tyr
    143 4 90,5 SM C16:1 20a-OH-C;His;Pro
    144 4 90,5 SM C16:1 Ac-Orn;Pro;SM (OH) C14:1
    145 4 90,4 SM C16:1 C5:1-DC;Histamine;SM (OH) C22:2
    146 4 90,3 SM C16:1 C5:1-DC;SM (OH) C14:1;Tyr
    147 4 90,3 SM C16:1 C5:1-DC;Orn;SM (OH) C16:1
    148 4 90,2 SM C16:1 Gln;Met;Pro
    149 4 90,1 SM C16:1 C5:1-DC;Histamine;Pro
    150 4 90,1 SM C16:1 20a-OH-C;Pro;SM (OH) C14:1
    151 4 90,1 SM C16:1 20a-OH-C;alpha-KGA;SM (OH) C22:2
    152 5 97,9 SM C16:1 20a-OH-C;Pro;SM (OH) C22:2;Trp
    153 5 93,7 SM C16:1 Ala;C5:1-DC;SM C16:0;SM (OH) C14:1
    154 5 93 SM C16:1 20a-OH-C;Arg;Leu;SM (OH) C14:1
    155 5 93 SM C16:1 Kynurenine;Leu;Met;SM (OH) C22:2
    156 5 92,8 SM C16:1 Met-SO;Pro;SM C24:0;Trp
    157 5 92,7 SM C16:1 Histamine;Kynurenine;SM (OH) C22:2;Tyr
    158 5 92,6 SM C16:1 Ac-Orn;Pro;SM C16:0;Trp
    159 5 92,3 SM C16:1 C10;His;Orn;TXB2
    160 5 92,1 SM C16:1 Arg;Cholestenone;Pro;Suc
    161 5 92,1 SM C16:1 C5:1-DC;Cholestenone;Gln;Lys
    162 5 91,9 SM C16:1 Kynurenine;Phe;Pro;SM (OH) C22:2
    163 5 91,4 SM C16:1 Gln;Met-SO;Orn;Pro
    164 5 91,3 SM C16:1 Ala;SM C18:1;SM (OH) C14:1;TXB2
    165 5 91 SM C16:1 20a-OH-C;Ser;SM (OH) C22:1;SM (OH) C22:2
    166 5 90,6 SM C16:1 Met-SO;Pro;SM C24:1;Trp
    167 5 90,6 SM C16:1 Ac-Orn;Pro;SM C24:0;SM (OH) C22:1
    168 5 90,5 SM C16:1 C5:1-DC;Orn;SM (OH) C16:1;SM (OH) C22:2
    169 5 90,5 SM C16:1 alpha-KGA;His;Kynurenine;Met-SO
    170 5 90,4 SM C16:1 Ac-Orn;Cholestenone;Pro;SM (OH) C14:1
    171 5 90,2 SM C16:1 C10;Kynurenine;SM C26:1;Tyr
    172 5 90,1 SM C16:1 Gln;Lac;Met-SO;SM (OH) C14:1
    173 5 90,1 SM C16:1 Ac-Orn;Pro;SM C24:0;SM (OH) C22:2
    174 6 96,5 SM C16:1 24-DH-Lanosterol;Arg;Creatinine;Met-SO;Trp
    175 6 96,2 SM C16:1 20a-OH-C;Fum;His;SM C26:1;Tyr
    176 6 94,5 SM C16:1 22R-OH-C;C6:1;Orn;Pro;SM (OH) C22:2
    177 6 91,6 SM C16:1 Gly;LTB4;Met-SO;SM (OH) C22:1;SM (OH) C22:2
    178 6 91,5 SM C16:1 20a-OH-C;24-DH-Lanosterol;Ile;Lys;SM (OH) C22:2
    179 6 90,9 SM C16:1 20a-OH-C;Gln;SM C18:1;SM (OH) C16:1;Tyr
    180 6 90,5 SM C16:1 His;Kynurenine;Met;Phe;SM (OH) C22:2
    181 7 92,9 SM C16:1 Ac-Orn;Ala;C6:1;Gln;Orn;SM (OH) C14:1
    Table 13: Combinations formed with a lead metabolite that correlate with the neurological behavioural score
    No Npar Accuracy Lead metabolite Additional metabolites
    1 3 95,2 Fum C5-DC (C6-OH);total DMA
    2 3 94 Fum 27-OH-C;Met-SO
    3 3 93,5 Fum 27-OH-C;Tyr
    4 3 92,2 Fum 27-OH-C;total DMA
    5 3 91,4 Fum C5:1;total DMA
    6 3 90,1 Fum 27-OH-C;Asp
    7 4 98,4 Fum C5-DC (C6-OH);total DMA;Tyr
    8 4 96,3 Fum 27-OH-C;Met-SO;SDMA
    9 4 96,3 Fum 27-OH-C;Cholestenone; Met-SO
    10 4 95,9 Fum C5-DC (C6-OH);SDMA;Tyr
    11 4 95,6 Fum C5:1;C8:1;total DMA
    12 4 95,6 Fum 27-OH-C;C5:1-DC;total DMA
    13 4 95,6 Fum 27-OH-C;Met-SO;Val
    14 4 95,5 Fum 27-OH-C;Met-SO;SM C16:1
    15 4 95,5 Fum 27-OH-C;C14:1-OH;Met-SO
    16 4 95,5 Fum 27-OH-C;C3-DC (C4-OH);Met-SO
    17 4 95,4 Fum 27-OH-C;C5:1;total DMA
    18 4 95,3 Fum 24-DH-Lanosterol;27-OH-C;Met-SO
    19 4 95,3 Fum 27-OH-C;Met-SO;total DMA
    20 4 95,2 Fum 27-OH-C;Asp;Carnosine
    21 4 95,2 Fum 27-OH-C;3b,5a,6b-THC;total DMA
    22 4 95,2 Fum 27-OH-C;Met-SO;Tyr
    23 4 95,1 Fum 27-OH-C;C10:2;Tyr
    24 4 95,1 Fum 27-OH-C;Lac;Met-SO
    25 4 94,8 Fum C14:1;C5:1;total DMA
    26 4 94,7 Fum 27-OH-C;Ala;total DMA
    27 4 94,7 Fum C5-DC (C6-OH);Met-SO;SDMA
    28 4 94,6 Fum 27-OH-C;C5:1-DC;SDMA
    29 4 94,6 Fum 27-OH-C;C4:1;Met-SO
    30 4 94,5 Fum 27-OH-C;CB:1;Met-SO
    31 4 94,4 Fum 27-OH-C;5a,6a-EpoxyC;Met-SO
    32 4 94,3 Fum 27-OH-C;SDMA;Tyr
    33 4 94,3 Fum 27-OH-C;Met-SO;Phe
    34 4 94,3 Fum 27-OH-C;Met;total DMA
    35 4 94,3 Fum 27-OH-C;C6 (C4:1-DC);Met-SO
    36 4 94,1 Fum 27-OH-C;C8:1;Tyr
    37 4 94 Fum 27-OH-C;Pent-P;Tyr
    38 4 94 Fum 27-OH-C;5a,6a-EpoxyC;Tyr
    39 4 93,9 Fum 27-OH-C;Pent-P;total DMA
    40 4 93,8 Fum 27-OH-C;Carnosine;Tyr
    41 4 93,6 Fum 27-OH-C;total DMA;Val
    42 4 93,6 Fum 27-OH-C;Cholestenone;Tyr
    43 4 93,5 Fum 27-OH-C;Phe;SDMA
    44 4 93,5 Fum 27-OH-C;Tyr;Val
    45 4 93,4 Fum 27-OH-C;total DMA;Trp
    46 4 93,3 Fum 27-OH-C;Lac;Tyr
    47 4 93,2 Fum 27-OH-C;Pro;total DMA
    48 4 93,1 Fum C10:2;C5-DC (C6-OH);Tyr
    49 4 93,1 Fum 27-OH-C;OAA;total DMA
    50 4 92,9 Fum 27-OH-C;8-iso-PGF2a;Phe
    51 4 92,7 Fum 27-OH-C;Ac-Orn;SDMA
    52 4 91,9 Fum 27-OH-C;SM C24:1;total DMA
    53 4 91,7 Fum 24-DH-Lanosterol;27-OH-C; Phe
    54 4 90,8 Fum C5:1;SDMA;SM (OH) C22:2
    55 4 90,7 Fum C14:1;Carnosine;Suc
    56 4 90,6 Fum C5-OH (C3-DC-M);Carnosine;total DMA
    57 4 90,5 Fum C10:2;C8:1;Phe
    58 4 90,4 Fum Carnosine;SDMA;Suc
    59 4 90,4 Fum C5:1;Met-SO;SDMA
    60 4 90,3 Fum C2;Carnosine;total DMA
    61 4 90,3 Fum C5-DC (C6-OH);C8:1;Met-SO
    62 4 90,2 Fum 27-OH-C;C5:1;SDMA
    63 4 90,2 Fum C4:1;C5-DC (C6-OH);Met-SO
    64 4 90,1 Fum 24,25-EpoxyC;C0;Met-SO
    65 4 90 Fum 27-OH-C;SDMA;Suc
    66 5 97,6 Fum 27-OH-C;C5:1;Met-SO;total DMA
    67 5 97,2 Fum 27-OH-C;C14:1-OH;Met-SO;total DMA
    68 5 96,6 Fum 27-OH-C;Cholestenone;Met-SO;SDMA
    69 5 94,7 Fum C10:2;C5-DC (C6-OH);Phe;SDMA
    70 5 94,6 Fum C14:1-OH;C5-DC (C6-OH);Carnosine;Met-SO
    71 5 93,8 Fum C5-DC (C6-OH);Cholestenone;Met-SO;SM C16:1
    72 5 93,4 Fum 24,25-EpoxyC;27-OH-C;C5:1;Met
    73 5 92,9 Fum C14:1-OH;C5:1;Carnosine;total DMA
    74 5 92,7 Fum Ac-Orn;C10:2;C6 (C4:1-DC);Carnosine
    75 5 92,4 Fum C4:1;C5:1;Met-SO;SDMA
    76 5 92,3 Fum C0;C10:2;Met-SO;total DMA
    77 5 91,3 Fum Ac-Orn;C6 (C4:1-DC);Pent-P;total DMA
    78 5 91,2 Fum C10:2;C14:1;Carnosine;Pent-P
    79 5 91 Fum 27-OH-C;Carnosine;Pent-P;SDMA
    80 5 90,9 Fum C0;Met-SO;SDMA;total DMA
    81 5 90,4 Fum Ac-Orn;C5-DC (C6-OH);SDMA;SM C16:1
    82 5 90,1 Fum C10:2;C14:1;C14:1-OH;Carnosine
    83 5 90,1 Fum 27-OH-C;Carnosine; DHA; Phe
    84 6 97,3 Fum C5:1;C5-DC (C6-OH);Phe;SDMA;total DMA
    85 6 96,4 Fum 27-OH-C;C5:1;His;SDMA;total DMA
    86 3 95,7 Carnosine C6 (C4:1-DC);Lac
    87 3 91,5 Carnosine C10:2;C14:1-OH
    88 3 91,2 Carnosine 27-OH-C;SM (OH) C22:2
    89 3 90,9 Carnosine C12;Lac
    90 4 95,2 Carnosine 27-OH-C;Asp;Fum
    91 4 95,2 Carnosine 27-OH-C;C6 (C4:1-DC);Met-SO
    92 4 95,1 Carnosine 27-OH-C;SM (OH) C14:1;Tyr
    93 4 94,5 Carnosine 27-OH-C;SM (OH) C22:2;total DMA
    94 4 94,3 Carnosine 27-OH-C;Ac-Orn;SM (OH) C14:1
    95 4 93,8 Carnosine C5-DC (C6-OH);SM (OH) C14:1;total DMA
    96 4 93,8 Carnosine 27-OH-C;Fum;Tyr
    97 4 93,5 Carnosine C10:2;C6 (C4:1-DC);Phe
    98 4 93,5 Carnosine C10:2;C14:1-OH;Lac
    99 4 91,7 Carnosine C5-DC (C6-OH);SM C16:0;total DMA
    100 4 91,4 Carnosine C5-DC (C6-OH);Phe;SM (OH) C14:1
    101 4 91,4 Carnosine C5-DC (C6-OH);SDMA;SM (OH) C22:2
    102 4 91,1 Carnosine C5-DC (C6-OH);Pent-P;SM (OH) C14:1
    103 4 91 Carnosine C5:1;SDMA;SM (OH) C14:1
    104 4 90,8 Carnosine 27-OH-C;SDMA;SM (OH) C22:2
    105 4 90,7 Carnosine C14:1;Fum;Suc
    106 4 90,6 Carnosine 27-OH-C;C14:1;Met-SO
    107 4 90,6 Carnosine C5-OH (C3-DC-M);Fum;total DMA
    108 4 90,5 Carnosine 24,25-EpoxyC;27-OH-C;Ac-Orn
    109 4 90,4 Carnosine Fum;SDMA;Suc
    110 4 90,4 Carnosine C5:1;C8:1;SM C16:1
    111 4 90,3 Carnosine C2;Fum;total DMA
    112 4 90,2 Carnosine C14:1;C5:1;SM C16:0
    113 4 90,2 Carnosine 24-DH-Lanosterol;27-OH-C;Lac
    114 5 97 Carnosine C10:2;C5-DC (C6-OH);C6 (C4:1-DC);Tyr
    115 5 95,3 Carnosine 27-OH-C;C10:2;C14:1;Met-SO
    116 5 94,6 Carnosine C14:1-OH;C5-DC (C6-OH);Fum;Met-SO
    117 5 94,4 Carnosine 27-OH-C;Phe;SM C16:1;total DMA
    118 5 92,9 Carnosine C14:1-OH;C5:1;Fum;total DMA
    119 5 92,7 Carnosine Ac-Orn;C10:2;C6 (C4:1-DC);Fum
    120 5 92,5 Carnosine 27-OH-C;C10:2;C8:1;Met
    121 5 91,7 Carnosine C5-DC (C6-OH);SM C16:1;SM C24:1;SM (OH) C22:2
    122 5 91,3 Carnosine 27-OH-C;C10:2;C8:1;His
    123 5 91,2 Carnosine C10:2;C14:1;Fum;Pent-P
    124 5 91,2 Carnosine 27-OH-C;Ac-Orn;SDMA;SM C16:1
    125 5 91 Carnosine 27-OH-C;Fum;Pent-P;SDMA
    126 5 90,4 Carnosine 24,25-EpoxyC;C5:1;Cholestenone;SM C24:1
    127 5 90,1 Carnosine C10:2;C14:1;C14:1-OH;Fum
    128 5 90,1 Carnosine C5-DC (C6-OH);SM (OH) C16:1;SM (OH) C22:2;Tyr
    129 5 90,1 Carnosine 27-OH-C;DHA;Fum;Phe
    130 5 90 Carnosine C5:1;SDMA;SM C16:0;SM (OH) C22:2
    131 4 91,2 24,25-EpoxyC C5:1;SM C24:1;total DMA
    132 4 90,5 24,25-EpoxyC 27-OH-C;C4:1;Met-SO
    133 4 90,5 24,25-EpoxyC 27-OH-C;Ac-Orn;Carnosine
    134 4 90,1 24,25-EpoxyC C5:1;Pent-P;total DMA
    135 4 90,1 24,25-EpoxyC CO;Fum;Met-SO
    136 5 93,4 24,25-EpoxyC 27-OH-C;C5:1;Fum;Met
    137 5 91,9 24,25-EpoxyC 27-OH-C;C5:1;Met;total DMA
    138 5 91,7 24,25-EpoxyC 27-OH-C;Lys;Met-SO;Suc
    139 5 90,4 24,25-EpoxyC C5:1;Carnosine;Cholestenone;SM C24:1
    140 6 96,2 24,25-EpoxyC C10:2;C5:1;C8:1;Phe;SM C24:1
    141 6 90,9 24,25-EpoxyC Ac-Orn;alpha-AAA;C5:1;C5-DC (C6-OH);total DMA
    142 3 90,2 alpha-AAA 27-OH-C;Met-SO
    143 4 94,4 alpha-AAA 27-OH-C;C5-DC (C6-OH);Met-SO
    Table 13: Combinations formed with a lead metabolite that correlate with the neurological behavioural score
    No Npar Accuracy Lead metabolite Additional metabolites
    144 6 90,9 alpha-AAA 24,25-EpoxyC;Ac-Orn;C5:1;C5-DC (C6-OH);total DMA
    145 3 91,4 SM (OH) C22:2 27-OH-C;total DMA
    146 3 91,2 SM (OH) C22:2 27-OH-C;Carnosine
    147 3 90,8 SM (OH) C22:2 C5-DC (C6-OH);total DMA
    148 3 90,6 SM (OH) C22:2 27-OH-C;Phe
    149 3 90,1 SM (OH) C22:2 C5:1;total DMA
    150 4 98,3 SM (OH) C22:2 27-OH-C;C5:1;total DMA
    151 4 97,1 SM (OH) C22:2 ; 27-OH-C;total DMA;Tyr
    152 4 94,5 SM (OH) C22:2 27-OH-C;Carnosine;total DMA
    153 4 91,9 SM (OH) C22:2 27-OH-C;C5:1;SDMA
    154 4 91,4 SM (OH) C22:2 C5-DC (C6-OH);Carnosine;SDMA
    155 4 91,3 SM (OH) C22:2 27-OH-C;C10:2;Thr
    156 4 90,8 SM (OH) C22:2 27-OH-C;Carnosine;SDMA
    157 4 90,8 SM (OH) C22:2 C5:1;Fum;SDMA
    158 4 90,6 SM (OH) C22:2 3b,5a,6b-THC;C5:1;SDMA
    159 5 91,7 SM (OH) C22:2 C5-DC (C6-OH);Carnosine;SM C16:1;SM C24:1
    160 5 90,7 SM (OH) C22:2 27-OH-C;SM (OH) C14:1;Thr;total DMA
    161 5 90,1 SM (OH) C22:2 C5-DC (C6-OH);Carnosine;SM (OH) C16:1;Tyr
    162 5 90 SM (OH) C22:2 C5:1;Carnosine;SDMA;SM C16:0
    163 6 91,8 SM (OH) C22:2 27-OH-C;C14:2-OH;C5-DC (C6-OH);Phe;SDMA

Claims (24)

  1. A diagnostic method for early assessing neonatal encephalopathy (NE) in a mammalian patient, which method comprises
    a) optionally obtaining a blood sample of said patient and
    b) assessing in said blood sample at least one panel of low molecular weight early metabolic markers indicative of the presence or absence of NE in said patient.
  2. The method of claim 1, wherein said mammalian patient is a human neonate.
  3. The method of claim 1, wherein said human neonate is suspected to suffer from neonatal encephalopathy.
  4. The method of one of the claims 2 and 3, wherein said blood sample is obtained immediately after birth or after resuscitation or suspicion of neonatal encephalopathy.
  5. The method of one of the preceding claims, wherein said neonatal encephalopathy affects basal ganglia and/or the hippocampus of the neonatal brain and/or causes neurological behavioural deficits of the child.
  6. The method of one of the preceding claims, wherein said panel of low molecular early metabolic markers indicative of the presence of neonatal encephalopathy comprises at least 2, like 2, 3, 4, 5, 6, or 7, different metabolites selected from at least one of the following classes of chemical substances:
    a) low molecular weight organic acids,
    b) sugars,
    c) acylcarnitines,
    d) sphingomyelins,
    e) amino acids,
    f) biogenic amines
    g) oxysterols, and
    h) prostaglandins
  7. The method of one of the preceding claims, wherein said panel of low molecular early metabolic markers indicative of the presence of neonatal encephalopathy comprises at least 2, like 2, 3, 4, 5, 6, or 7,metabolites selected from at least one of the following functional classes of metabolites
    a) energy metabolism related metabolites indicating the occurrence or previous lack of oxygen
    b) metabolites of oxidative stress and anti-oxidative capacities
    c) metabolites with neurotoxic or neuroprotective potential,
    d) metabolites predominantly occurring in the brain.
  8. The method of one of the preceding claims, wherein said panel is indicative of the presence of neonatal encephalopathy with high statistic significance, in particular an accuracy of at least 75, more particular at least about 80 as determined in a non-human animal model.
  9. The method of one of the preceding claims, wherein said chemical classes of metabolites comprise the following individual members:
    a) low molecular weight organic acids, selected from dicarboxylic acids, like alpha-ketoglutaric acid, fumaric acid and succinic acid; and monocarboxylic acids, like lactic acid;
    b) sugars, selected from like hexoses and hexosephosphates, like glucose-1-phosphate, glucose-6-phosphate, fructose-6-phosphate and pentose phospates, like ribose-5-phosphate and ribulose-5-phosphate;
    c) carnitine (free), acylcarnitines, like, decadienoylcarnitine, tetradecenoylcarnitine, 3-hydroxytetradecenoylcarnitine, tetradecadienoylcarnitine, 3-hydroxytetradecadienoylcarnitine, hexadecadienoylcarnitine, 3-hydroxybutyrylcarnitine, 3-hydroxyisovalerylcarnitine / 3-hydroxy-2-methylbutyrylcarnitine, butenoylcarnitine, tiglylcarnitine, glutaconylcarnitine, mesaconylcarnitine (undecanoylcarnitine ), glutarylcarnitine, hexenoylcarnitine, hexanoylcarnitine, octenoylcarnitine;
    d) sphingomyelins, like sphingomyelin with acyl residue sum C16:0, sphingomyelin with acyl residue sum C16:1, sphingomyelin with acyl residue sum C18:0, sphingomyelin with acyl residue sum C18:1, sphingomyelin with acyl residue sum C20:2, sphingomyelin with acyl residue sum C24:0, sphingomyelin with acyl residue sum C24:1, sphingomyelin with acyl residue sum C26:0 and sphingomyelin with acyl residue sum C26:1, hydroxysphingomyelin with acyl residue sum C14:1, hydroxysphingomyelin with acyl residue sum C16:1, hydroxysphingomyelin with acyl residue sum C22:1, hydroxysphingomyelin with acyl residue sum C22:2, hydroxysphingomyelin with acyl residue sum C24:1;
    e) amino acids, like alanine, arginine, asparagine, citrulline, glutamine, glycine, histidine, leucine, lysine, methionine, ornithine, phenylalanine, proline, serine, threonine, tryptophane, tyrosine and valine;
    f) biogenic amines, like N-acetylornithine, asymmetric dimethylarginine, 2-aminoadipic acid, carnosine, creatinine, histamine, kynurenine, methionine-sulfoxide, symmetric dimethylarginine and total dimethylarginine;
    g) oxysterols, like 20α -hydroxycholesterol, 24,25-epoxycholesterol, 24-dihydrolanosterol, 24-S-hydroxycholesterol, 25-hydroxycholesterol, 27-hydroxycholesterol, 5α ,6α -epoxycholesterol, cholestenone, and 3ß,5α ,6ß-trihydroxycholestan; and
    h) prostaglandins, like 8-iso-prostaglandin F2alpha, leukotriene B4 and tromboxane B2.
  10. The method of one of the preceding claims, wherein said functional classes of metabolites comprise the following individual members:
    a) energy metabolism related metabolites indicating the occurrence or previous lack of oxygen, like alanine, fumarate, succinate, alpha-ketoglutaric acid , decadienoyl carnitines and mesaconylcarnitine;
    b) metabolites of oxidative stress and anti-oxidative capacities and inflammation, like methionine-sulfoxide , hydroxysphingomyelins and spingomyelins;
    c) metabolites with neurotoxic or neuroprotective potential, like 2-aminoadipic acid , carnosine, kynurenine; and
    d) metabolites predominantly occurring in the brain, like 25-hydroxycholesterol, 24-hydroxycholesterol, 24,25-epoxycholesterol.
  11. The method of one of the preceding claims, wherein said at least one, like 1 to 100, 1 to 50, 1 to 25, 1 to 10, or 2, 3, 4, 5 or 6 panels indicative of the presence of NE, are selected within one of the following sets of models:
    a) set of hippocampus damage-related models 1 to 145 of Table 8;
    b) set of basal ganglia damage-related models 1 to 3945 of Table 9; or
    c) set of neurological behavioural abnormality-related models 1 to 717 of Table 10.
  12. The method of one of the preceding claims, wherein said panel of markers indicative of the presence of NE comprises at least one first marker (lead marker), like 1, 2, 3, 4, 5, 6, or 7 lead markers selected form:
    a) fumarate (Fum);
    b) carnosine (Car);
    c) 24,25-epoxycholesterol (24,25 EpoxyC);
    d) alpha-aminoadipic acid (alpha-AAA);
    e) hydroxysphingomyelin with acyl residue sum C22:2(SM(OH) C22:2);
    f) methionine-sulfoxide (Met-SO);
    g) hydroxysphingomyelin with acyl residue sum C14:1 (SM(OH) C14:1);
    h) alpha-ketoglutaric acid(alpha-KGA);
    i) cholestenone;
    k) sphingomyelin with acyl residue sum C16:1 (SM C16:1);
    l) decadienoyl carnitine (C10:2);
    m) sphingomyelin with acyl residue sum C24:1 (SM C24:1);
    n) mesaconylcarnitine (C5:1-DC); and
    o) succinate (Suc).
    optionally in combination with at least one, like 1, 2, 3, 4, 5, or 6, second marker different from said lead markers and selected from the markers as defined in anyone of said claims 6 to 9.
  13. The method of claim 12, wherein
    a) hippocampus damage-related panels comprise as lead marker C10:2; SM C24:1; C5:1-DC and/or Suc;
    b) basal ganglia damage-related panels comprise as lead marker Met-SO; SM(OH) C14:1; alpha-KGA, Cholestenone and/or SM C16:1; and
    c) neurological behavioural abnormality-related panels comprise as lead marker Fum; Car; 24,25-EpoxyC; alpha-AAA; and/or SM(OH) C22:2.
  14. The method of claim 13, wherein said panels are selected from one of the following sets of panels:
    a) set of hippocampus damage-related panels 1 to 25 of Table 11;
    b) set of basal ganglia damage-related panels 1 to 181 of Table 12 ; or
    c) set of neurological behavioural abnormality-related panels 1 to 163 of Table 13.
  15. The method of one of the preceding claims, wherein the metabolites are detected by nuclear magnetic resonance spectroscopy (NMR), mass spectroscopy, ELISA, fluorescence labeling techniques, flow cytometry, chromatography, capillary electrophoresis or chemical sensor or combinations thereof.
  16. A diagnostic method for early differentiating types of brain damage, selected from damages of the brain compartments hippocampus and basal ganglia, in human neonates, which method comprises
    a) optionally obtaining a blood sample of said neonate and
    b) assessing in said body fluid sample at least one panel of low molecular early metabolic markers indicative of the presence of brain injury in a brain compartment, selected from hippocampus and basal ganglia; in particular et least one panel selected from panels of hippocampus damage-related panels 1 to 145 of Table 8 or 1 to 25 of Table 11; and basal ganglia damage-related panels 1 to 3945 of Table 9 or 1 to 181 of Table 12.
  17. A diagnostic method for early predicting a neurological behavioural abnormality caused by neonatal encephalopathy in human neonates, which method comprises
    a) optionally obtaining a body fluid (blood, serum) sample of said neonate and
    b) assessing in said body fluid sample at least one panel of low molecular early metabolic markers indicative of neonatal encephalopathy-related neurological behavioural abnormality, in particular et least one panel selected from panels 1 to 717 of Table 10 or 1 to 183 of Table 13.
  18. The method of one of the preceding claims, wherein assessing said blood sample comprises:
    a) detecting said panel of metabolites;
    b) determining a profile of said detected metabolites; and
    c) comparing the profile of the detected metabolites to a standard metabolite profile, thereby diagnosing said disease or damage.
  19. The method of one of the preceding claims, wherein an increase or decrease of at least one of said metabolites of said at least one panel is observed.
  20. A method of assessing the progression or regression of neonatal encephalopathy which method comprises performing a diagnostic method of any one of the claims 1 to 19, repeating said method at least once, and comparing the obtained set of analytical parameter for said panel of biomarkers with the previously determined set.
  21. A method of treating a mammalian patient, in particular human neonate suffering from neonatal encephalopathy, which method comprising
    a) performing a diagnostic method of anyone of the claims 1 to 19
    b) treating a mammalian patient, in particular a neonate who as been positively assessed for neonatal encephalopathy, in order to reduce disease symptoms.
  22. The method of claim 21, wherein said treatment comprises hypothermia.
  23. A panel of early metabolic biomarkers as defined in anyone of the Tables 8, 9, 10, 11, 12 and 13 for use in diagnosis.
  24. A kit for assessing in a blood sample of a mammalian patient the disease state of a neonatal encephalopathy comprising:
    a) means for measuring a panel of low molecular early metabolic markers indicative of the presence of neonatal encephalopathy, wherein the biomarkers or panels thereof as defined in anyone of the claims 3 to 19;
    b) at least one standard panel of low molecular early metabolic markers indicative of healthy brain, and/or at least one standard panel of low molecular early metabolic markers indicative of a certain state of progression or regression of neonatal encephalopathy; and
    c) means for identifying the disease state based on a comparison of the biomarker panel of the patient and the standard panel.
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EP3546938A1 (en) * 2018-03-30 2019-10-02 Université d'Angers Metabolic signature and use thereof for the diagnosis of glaucoma
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